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Teves L, Vieira Melo AR, Ferreira AF, Raposo M, Lemos C, Bettencourt C, Lima M. Global DNA methylation is not elevated in blood samples from Machado-Joseph disease mutation carriers. Epigenetics 2024; 19:2368995. [PMID: 38900099 PMCID: PMC11195492 DOI: 10.1080/15592294.2024.2368995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 06/12/2024] [Indexed: 06/21/2024] Open
Abstract
Machado-Joseph disease (MJD) is an autosomal dominant spinocerebellar ataxia (SCA) caused by a polyglutamine expansion in the ataxin-3 protein, which initiates a cascade of pathogenic events, including transcriptional dysregulation. Genotype-phenotype correlations in MJD are incomplete, suggesting an influence of additional factors, such as epigenetic modifications, underlying the MJD pathogenesis. DNA methylation is known to impact the pathophysiology of neurodegenerative disorders through gene expression regulation and increased methylation has been reported for other SCAs. In this work we aimed to analyse global methylation in MJD carriers. Global 5-mC levels were quantified in blood samples of 33 MJD mutation carriers (patients and preclinical subjects) and 33 healthy controls, matched by age, sex, and smoking status. For a subset of 16 MJD subjects, a pilot follow-up analysis with two time points was also conducted. No differences were found in median global 5-mC levels between MJD mutation carriers and controls and no correlations between methylation levels and clinical or genetic variables were detected. Also, no alterations in global 5-mC levels were observed over time. Our findings do not support an increase in global blood methylation levels associated with MJD.
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Affiliation(s)
- Luís Teves
- Faculdade de Ciências e Tecnologia, Universidade dos Açores, Ponta Delgada, Portugal
- Instituto Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
- UnIGENe, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Ana Rosa Vieira Melo
- Faculdade de Ciências e Tecnologia, Universidade dos Açores, Ponta Delgada, Portugal
| | - Ana F. Ferreira
- Faculdade de Ciências e Tecnologia, Universidade dos Açores, Ponta Delgada, Portugal
| | - Mafalda Raposo
- UnIGENe, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Carolina Lemos
- Instituto Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
- UnIGENe, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Conceição Bettencourt
- Department of Neurodegenerative Disease and Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
| | - Manuela Lima
- Faculdade de Ciências e Tecnologia, Universidade dos Açores, Ponta Delgada, Portugal
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2
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Rilling JK, Lee M, Zhou C, Gonzalez A, Lindo J. Grandmotherhood is associated with reduced OXTR DNA methylation. Psychoneuroendocrinology 2024; 168:107122. [PMID: 39002451 DOI: 10.1016/j.psyneuen.2024.107122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/14/2024] [Accepted: 07/01/2024] [Indexed: 07/15/2024]
Abstract
In mammals, both parental and alloparental care are associated with increased brain oxytocin signaling. Grandmothers are important alloparents in many human families. Based on animal model research showing that peripheral Oxtr methylation is associated with Oxtr expression in the nucleus accumbens, we investigated whether grandmaternal caregiving is associated with lower peripheral OXTR methylation. Results reveal several regions within OXTR where grandmothers have lower DNA methylation compared with non-grandmother controls, and no regions where grandmothers have higher OXTR DNA methylation. Among grandmothers, OXTR methylation was most strongly correlated with the grandmother's assessment of the degree of positive feelings between her and the grandchild, which in turn predicted caregiving engagement. Although there was little evidence that grandmaternal OXTR methylation modulated grandmaternal neural responses to viewing photos of the grandchild within brain regions involved in caregiving motivation, it was negatively correlated with the neural response to an unknown grandchild. Thus, while OT signaling may not be essential for activating grandmaternal brain reward systems in our low-stress experimental context, it may support caregiving motivation towards unrelated children. Future longitudinal research should determine whether the transition to grandmotherhood is associated with a reduction in OXTR methylation.
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Affiliation(s)
- James K Rilling
- Department of Psychology, Emory University, United States; Department of Psychiatry and Behavioral Sciences, Emory University, United States; Center for Behavioral Neuroscience, Emory University, United States; Emory National Primate Research Center, Emory University, United States; Center for Translational Social Neuroscience, Emory University, United States.
| | - Minwoo Lee
- Department of Anthropology, Emory University, United States
| | - Carolyn Zhou
- Department of Anthropology, Emory University, United States
| | - Amber Gonzalez
- Department of Anthropology, Emory University, United States
| | - John Lindo
- Department of Anthropology, Emory University, United States
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3
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Dermawan JK, Malik F, Gross JM, Baraban E, Pratilas C, Mneimneh W, Trucco M, Sun W, Barr FG, D'Almeida Costa F, Fritchie KJ. Novel PAX3::MAML3 fusion identified in alveolar rhabdomyosarcoma, using DNA methylation profiling to expand the genetic spectrum of "fusion-positive" cases. Mod Pathol 2024:100594. [PMID: 39147032 DOI: 10.1016/j.modpat.2024.100594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/28/2024] [Accepted: 08/08/2024] [Indexed: 08/17/2024]
Abstract
Alveolar rhabdomyosarcoma (ARMS) with FOXO1 gene rearrangements is an aggressive pediatric rhabdomyosarcoma subtype that is prognostically distinct from embryonal rhabdomyosarcoma and fusion-negative ARMS. Herein, we report two cases of ARMS with PAX3::MAML3 fusions. The tumors arose in an infant and an adolescent as stage IV metastatic disease (by Children's Oncology Group staging system). Histologically, both cases were small round blue cell tumors arranged in vague nests and solid sheets that were diffusely positive for desmin and myogenin. By methylation profiling and unsupervised clustering analysis, the tumors clustered with ARMS with classic FOXO1 rearrangements and ARMS with variant PAX3::NCOA1/INO80D fusions, but not with biphenotypic sinonasal sarcoma (BSNS) with PAX3::MAML3/NCOA2/FOXO1/YAP1 fusions, nor with other small round blue cell tumors, including embryonal rhabdomyosarcoma. The differentially methylated genes between ARMS and BSNS were highly enriched in genes involved in myogenesis, and 21% of these genes overlap with target genes of the PAX3::FOXO1 fusion transcription factor. On follow-up after initiation of vincristine/actinomycin/cyclophosphamide chemotherapy, the tumors showed partial and complete clinical response, consistent with typical upfront chemotherapy responsiveness of ARMS with the classic FOXO1 rearrangement. We conclude that PAX3::MAML3 is a novel variant fusion of ARMS, which displays a methylation signature distinct from BSNS despite sharing similar PAX3 fusions. These findings highlight the utility of methylation profiling in classifying ARMS with non-canonical fusions.
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Affiliation(s)
- Josephine K Dermawan
- Department of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Faizan Malik
- Department of Pathology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - John M Gross
- Department of Pathology, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Ezra Baraban
- Department of Pathology, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Christine Pratilas
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins Hospital, Baltimore, MD, USA
| | - Wadad Mneimneh
- Department of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Matteo Trucco
- Department of Pediatric Hematology, Oncology & Bone Marrow Transplant, Cleveland Clinic, Cleveland, OH, USA
| | - Wenyue Sun
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Frederic G Barr
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | | | - Karen J Fritchie
- Department of Pathology and Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.
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4
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Choi MK, Cook A, Mungikar K, Eachus H, Tochwin A, Linke M, Gerber S, Ryu S. Exposure to elevated glucocorticoid during development primes altered transcriptional responses to acute stress in adulthood. iScience 2024; 27:110160. [PMID: 38989456 PMCID: PMC11233911 DOI: 10.1016/j.isci.2024.110160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/02/2024] [Accepted: 05/29/2024] [Indexed: 07/12/2024] Open
Abstract
Early life stress (ELS) is a major risk factor for developing psychiatric disorders, with glucocorticoids (GCs) implicated in mediating its effects in shaping adult phenotypes. In this process, exposure to high levels of developmental GC (hdGC) is thought to induce molecular changes that prime differential adult responses. However, identities of molecules targeted by hdGC exposure are not completely known. Here, we describe lifelong molecular consequences of hdGC exposure using a newly developed zebrafish double-hit stress model, which shows altered behaviors and stress hypersensitivity in adulthood. We identify a set of primed genes displaying altered expression only upon acute stress in hdGC-exposed adult fish brains. Interestingly, this gene set is enriched in risk factors for psychiatric disorders in humans. Lastly, we identify altered epigenetic regulatory elements following hdGC exposure. Thus, our study provides comprehensive datasets delineating potential molecular targets mediating the impact of hdGC exposure on adult responses.
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Affiliation(s)
- Min-Kyeung Choi
- Living Systems Institute & Department of Clinical and Biomedical Sciences, University of Exeter, Stocker Road, EX4 4QD Exeter, UK
| | - Alexander Cook
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University Mainz, Langenbeckstraße 1, 55131 Mainz, Germany
| | - Kanak Mungikar
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University Mainz, Langenbeckstraße 1, 55131 Mainz, Germany
| | - Helen Eachus
- Living Systems Institute & Department of Clinical and Biomedical Sciences, University of Exeter, Stocker Road, EX4 4QD Exeter, UK
| | - Anna Tochwin
- Living Systems Institute & Department of Clinical and Biomedical Sciences, University of Exeter, Stocker Road, EX4 4QD Exeter, UK
| | - Matthias Linke
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University Mainz, Langenbeckstraße 1, 55131 Mainz, Germany
| | - Susanne Gerber
- Institute of Human Genetics, University Medical Center, Johannes Gutenberg University Mainz, Langenbeckstraße 1, 55131 Mainz, Germany
| | - Soojin Ryu
- Living Systems Institute & Department of Clinical and Biomedical Sciences, University of Exeter, Stocker Road, EX4 4QD Exeter, UK
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Katrinli S, Wani AH, Maihofer AX, Ratanatharathorn A, Daskalakis NP, Montalvo-Ortiz J, Núñez-Ríos DL, Zannas AS, Zhao X, Aiello AE, Ashley-Koch AE, Avetyan D, Baker DG, Beckham JC, Boks MP, Brick LA, Bromet E, Champagne FA, Chen CY, Dalvie S, Dennis MF, Fatumo S, Fortier C, Galea S, Garrett ME, Geuze E, Grant G, Hauser MA, Hayes JP, Hemmings SM, Huber BR, Jajoo A, Jansen S, Kessler RC, Kimbrel NA, King AP, Kleinman JE, Koen N, Koenen KC, Kuan PF, Liberzon I, Linnstaedt SD, Lori A, Luft BJ, Luykx JJ, Marx CE, McLean SA, Mehta D, Milberg W, Miller MW, Mufford MS, Musanabaganwa C, Mutabaruka J, Mutesa L, Nemeroff CB, Nugent NR, Orcutt HK, Qin XJ, Rauch SAM, Ressler KJ, Risbrough VB, Rutembesa E, Rutten BPF, Seedat S, Stein DJ, Stein MB, Toikumo S, Ursano RJ, Uwineza A, Verfaellie MH, Vermetten E, Vinkers CH, Ware EB, Wildman DE, Wolf EJ, Young RM, Zhao Y, van den Heuvel LL, Uddin M, Nievergelt CM, Smith AK, Logue MW. Epigenome-wide association studies identify novel DNA methylation sites associated with PTSD: A meta-analysis of 23 military and civilian cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.15.24310422. [PMID: 39072012 PMCID: PMC11275670 DOI: 10.1101/2024.07.15.24310422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Background The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions. Methods As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using either Illumina HumanMethylation450 or MethylationEPIC (850K) BeadChips. A common QC pipeline was applied. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress. Results We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e-09 < p < 5.30e-08), as well as 14 associated in analyses of specific strata (military vs civilian cohort, sex, and ancestry), including CpGs in AHRR and CDC42BPB . Many of these loci exhibit blood-brain correlation in methylation levels and cross-tissue associations with PTSD in multiple brain regions. Methylation at most CpGs correlated with their annotated gene expression levels. Conclusions This study identifies 11 PTSD-associated CpGs, also leverages data from postmortem brain samples, GWAS, and genome-wide expression data to interpret the biology underlying these associations and prioritize genes whose regulation differs in those with PTSD.
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Yusipov I, Kalyakulina A, Trukhanov A, Franceschi C, Ivanchenko M. Map of epigenetic age acceleration: A worldwide analysis. Ageing Res Rev 2024; 100:102418. [PMID: 39002646 DOI: 10.1016/j.arr.2024.102418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 07/03/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.
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Affiliation(s)
- Igor Yusipov
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Alena Kalyakulina
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Arseniy Trukhanov
- Mriya Life Institute, National Academy of Active Longevity, Moscow 124489, Russia.
| | - Claudio Franceschi
- Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
| | - Mikhail Ivanchenko
- Artificial Intelligence Research Center, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia; Institute of Biogerontology, Lobachevsky State University, Nizhny Novgorod 603022, Russia.
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7
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Patel D, McElroy JP, Weng DY, Sahar K, Reisinger SA, Freudenheim JL, Wewers MD, Shields PG, Song MA. Sex-related DNA methylation is associated with inflammation and gene expression in the lungs of healthy individuals. Sci Rep 2024; 14:14280. [PMID: 38902313 PMCID: PMC11190195 DOI: 10.1038/s41598-024-65027-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024] Open
Abstract
Lung cancer exhibits sex-biased molecular characteristics and epidemiological trends, suggesting a need for sex-specific approaches to understanding its etiology and treatment. DNA methylation alterations play critical roles in lung carcinogenesis and may serve as valuable biomarkers for precision medicine strategies. We employed the Infinium MethylationEPIC array to identify autosomal sex-related differentially methylated CpG sites (DM-CpGs) in lung epithelium of healthy individuals (32 females and 37 males) while controlling for age, BMI, and tobacco use. We correlated DM-CpGs with gene expression in lung epithelium and immune responses in bronchoalveolar lavage. We validated these DM-CpGs in lung tumors and adjacent normal tissue from The Cancer Genome Atlas (TCGA). Among 522 identified DM-CpGs, 61% were hypermethylated in females, predominantly located in promoter regions. These DM genes were implicated in cell-to-cell signaling, cellular function, transport, and lipid metabolism. Correlation analysis revealed sex-specific patterns between DM-CpGs and gene expression. Additionally, several DM-CpGs were correlated significantly with cytokines (IL-1β, IL-4, IL-12p70, and IFN-γ), macrophage, and lymphocyte counts. Also, some DM-CpGs were observed in TCGA lung adenocarcinoma, squamous cell carcinoma, and adjacent normal tissues. Our findings highlight sex-specific DNA methylation patterns in healthy lung epithelium and their associations with lung gene expression and lung immune biomarkers. These findings underscore the potential role of lung sex-related CpGs as epigenetic predispositions influencing sex disparities in lung cancer risk and outcomes, warranting further investigation for personalized lung cancer management strategies.
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Affiliation(s)
- Devki Patel
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Joseph P McElroy
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH, USA
| | - Daniel Y Weng
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH, USA
| | - Kamel Sahar
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH, USA
| | - Sarah A Reisinger
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH, USA
| | - Jo L Freudenheim
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA
| | - Mark D Wewers
- Pulmonary and Critical Care Medicine, Department of Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - Peter G Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH, USA.
- Comprehensive Cancer Center, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
| | - Min-Ae Song
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA.
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8
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Nair VD, Pincas H, Smith GR, Zaslavsky E, Ge Y, Amper MAS, Vasoya M, Chikina M, Sun Y, Raja AN, Mao W, Gay NR, Esser KA, Smith KS, Zhao B, Wiel L, Singh A, Lindholm ME, Amar D, Montgomery S, Snyder MP, Walsh MJ, Sealfon SC. Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures. CELL GENOMICS 2024; 4:100421. [PMID: 38697122 PMCID: PMC11228891 DOI: 10.1016/j.xgen.2023.100421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/07/2023] [Accepted: 09/12/2023] [Indexed: 05/04/2024]
Abstract
Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8 weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.
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Affiliation(s)
- Venugopalan D Nair
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hanna Pincas
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gregory R Smith
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yongchao Ge
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mary Anne S Amper
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mital Vasoya
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Maria Chikina
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yifei Sun
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Weiguang Mao
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicole R Gay
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Karyn A Esser
- Department of Physiology and Aging, University of Florida, Gainesville, FL 32610, USA
| | - Kevin S Smith
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Bingqing Zhao
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Laurens Wiel
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Aditya Singh
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Malene E Lindholm
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - David Amar
- Department of Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Stephen Montgomery
- Departments of Pathology and Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Martin J Walsh
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Stuart C Sealfon
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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9
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Domingo-Relloso A, Tellez-Plaza M, Valeri L. Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology. Curr Environ Health Rep 2024; 11:109-117. [PMID: 38386268 DOI: 10.1007/s40572-024-00436-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
PURPOSE OF REVIEW Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data. RECENT FINDINGS The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Biostatistics, Columbia University Mailman School of Public Health, 722 West 168Th Street, New York, NY, 10032, USA.
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Linda Valeri
- Department of Biostatistics, Columbia University Mailman School of Public Health, 722 West 168Th Street, New York, NY, 10032, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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10
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Frazer LC, Yamaguchi Y, Singh DK, Akopyants NS, Good M. DNA methylation in necrotizing enterocolitis. Expert Rev Mol Med 2024; 26:e16. [PMID: 38557638 PMCID: PMC11140546 DOI: 10.1017/erm.2024.16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 03/05/2024] [Accepted: 03/26/2024] [Indexed: 04/04/2024]
Abstract
Epigenetic modifications, such as DNA methylation, are enzymatically regulated processes that directly impact gene expression patterns. In early life, they are central to developmental programming and have also been implicated in regulating inflammatory responses. Research into the role of epigenetics in neonatal health is limited, but there is a growing body of literature related to the role of DNA methylation patterns and diseases of prematurity, such as the intestinal disease necrotizing enterocolitis (NEC). NEC is a severe intestinal inflammatory disease, but the key factors that precede disease development remain to be determined. This knowledge gap has led to a failure to design effective targeted therapies and identify specific biomarkers of disease. Recent literature has identified altered DNA methylation patterns in the stool and intestinal tissue of neonates with NEC. These findings provide the foundation for a new avenue in NEC research. In this review, we will provide a general overview of DNA methylation and then specifically discuss the recent literature related to methylation patterns in neonates with NEC. We will also discuss how DNA methylation is used as a biomarker for other disease states and how, with further research, methylation patterns may serve as potential biomarkers for NEC.
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Affiliation(s)
- Lauren C. Frazer
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yukihiro Yamaguchi
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Dhirendra K. Singh
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Natalia S. Akopyants
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Misty Good
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Kim H, Joo MW, Yoon J, Park HS, Kim JH, Lee JH, Kim SH, Lee SK, Chung YG, Cho YJ. Can DNA Methylation Profiling Classify Histologic Subtypes and Grades in Soft Tissue Sarcoma? Clin Orthop Relat Res 2024; 482:00003086-990000000-01545. [PMID: 38517415 PMCID: PMC11124674 DOI: 10.1097/corr.0000000000003041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 02/21/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND A clear classification of the subtype and grade of soft tissue sarcoma is important for predicting prognosis and establishing treatment strategies. However, the rarity and heterogeneity of these tumors often make diagnosis difficult. In addition, it remains challenging to predict the response to chemotherapy and prognosis. Thus, we need a new method to help diagnose soft tissue sarcomas and determine treatment strategies in conjunction with traditional methods. Genetic alterations can be found in some subtypes of soft tissue sarcoma, but many other types show dysregulated gene expression attributed to epigenetic changes, such as DNA methylation status. However, research on DNA methylation profiles in soft tissue sarcoma is still insufficient to provide information to assist in diagnosis and therapeutic decisions. QUESTIONS/PURPOSES (1) Do DNA methylation profiles differ between normal tissue and soft tissue sarcoma? (2) Do DNA methylation profiles vary between different histologic subtypes of soft tissue sarcoma? (3) Do DNA methylation profiles differ based on tumor grade? METHODS Between January 2019 and December 2022, we treated 85 patients for soft tissue sarcomas. We considered patients whose specimens were approved for pilot research by the Human Biobank of St. Vincent's Hospital, The Catholic University of Korea, as potentially eligible. Based on this, 41% (35 patients) were eligible; 1% (one patient) was excluded because of gender mismatch between clinical and genetic data after controlling for data quality. Finally, 39 specimens (34 soft tissue sarcomas and five normal samples) were included from 34 patients who had clinical data. All tissue samples were collected intraoperatively. The five normal tissue samples were from muscle tissues. There were 20 female patients and 14 male patients, with a median age of 58 years (range 19 to 82 years). Genomic DNA was extracted from frozen tissue, and DNA methylation profiles were obtained. Genomic annotation of DNA methylation sites and hierarchical cluster analysis were performed to interpret results from DNA methylation profiling. A t-test was used to analyze different methylation probes. Benjamini-Hochberg-adjusted p value calculations were used to account for bias resulting from evaluating thousands of methylation sites. RESULTS The most common histologic subtypes were liposarcoma (n = 10) and leiomyosarcoma (n = 9). The tumor grade was Fédération Nationale des Centres de Lutte Contre Le Cancer Grades 1, 2, and 3 in 3, 15, and 16 patients, respectively. DNA methylation profiling demonstrated differences between soft tissue sarcoma and normal tissue as 21,188 cytosine-phosphate-guanine sites. Despite the small number of samples, 72 of these sites showed an adjusted p value of < 0.000001, suggesting a low probability of statistical errors. Among the 72 sites, 70 exhibited a hypermethylation pattern in soft tissue sarcoma, with only two sites showing a hypomethylation pattern. Thirty of 34 soft tissue sarcomas were distinguished from normal samples using hierarchical cluster analysis. There was a different methylation pattern between leiomyosarcoma and liposarcoma at 7445 sites. Using the data, hierarchical clustering analysis showed that liposarcoma was distinguished from leiomyosarcoma. When we used the same approach and included other subtypes with three or more samples, only leiomyosarcoma and myxofibrosarcoma were separated from the other subtypes, while liposarcoma and alveolar soft-part sarcoma were mixed with the others. When comparing DNA methylation profiles between low-grade (Grade 1) and high-grade (Grades 2 and 3) soft tissue sarcomas, a difference in methylation pattern was observed at 144 cytosine-phosphate-guanine sites. Among these, 132 cytosine-phosphate-guanine sites exhibited hypermethylation in the high-grade group compared with the low-grade group. Hierarchical clustering analysis showed a division into two groups, with most high-grade sarcomas (28 of 31) separated from the low-grade group and few (3 out of 31) clustered together with the low-grade group. However, three high-grade soft tissue sarcomas were grouped with the Grade 1 cluster, and all of these sarcomas were Grade 2. When comparing Grades 1 and 2 to Grade 3, Grade 3 tumors were separated from Grades 1 and 2. CONCLUSION We observed a different DNA methylation pattern between soft tissue sarcomas and normal tissues. Liposarcoma was distinguished from leiomyosarcoma using methylation profiling. High-grade soft tissue sarcoma samples showed a hypermethylation pattern compared with low-grade ones. Our findings indicate the need for research using methylation profiling to better understand the diverse biological characteristics of soft tissue sarcoma. Such research should include studies with sufficient samples and a variety of subtypes, as well as analyses of the expression and function of related genes. Additionally, efforts to link this research with clinical data related to treatment and prognosis are necessary. LEVEL OF EVIDENCE Level III, diagnostic study.
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Affiliation(s)
- Hyunho Kim
- Division of Medical Oncology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Min Wook Joo
- Department of Orthopedic Surgery, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Joohee Yoon
- Department of Obstetrics and Gynecology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hong Sik Park
- Deparment of Hospital Pathology, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - June Hyuk Kim
- Orthopaedic Oncology Clinic, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea
| | - Joo Hwan Lee
- Deparment of Radiation Oncology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung Hwan Kim
- Deparment of Radiation Oncology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Seul Ki Lee
- Deparment of Radiology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yang-Guk Chung
- Department of Orthopedic Surgery, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yoon Joo Cho
- Department of Orthopedic Surgery, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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Wang F, Hu D, Lou X, Wang Y, Wang L, Zhang T, Yan Z, Meng N, Zou Y. BNIP3 and DAPK1 methylation in peripheral blood leucocytes are noninvasive biomarkers for gastric cancer. Gene 2024; 898:148109. [PMID: 38142898 DOI: 10.1016/j.gene.2023.148109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 12/26/2023]
Abstract
OBJECTIVE The objective of this study is to comprehensively investigate the potential value of BNIP3 and DAPK1 methylation in peripheral blood leukocytes as a non-invasive biomarker for the detection of gastric cancer (GC), prediction of chemotherapy efficacy, and prognosis assessment. PATIENTS AND METHODS Initially, multiple bioinformatic analyses were employed to explore the genetic landscape and biological effects of BNIP3 and DAPK1 in GC tissues. Subsequently, case-control and prospective follow-up studies were conducted to compare the differences in BNIP3 and DAPK1 methylation levels in peripheral blood leukocytes among GC patients and healthy controls, as well as between patients exhibiting sensitivity and resistance to platinum plus fluorouracil treatment, and between patients with varying survival outcomes of GC. Additionally, several predictive nomograms were constructed based on the identified CpG sites and relevant clinical parameters to forecast the occurrence of GC, chemotherapy efficacy, and prognosis. RESULTS The upregulation of BNIP3 and DAPK1 was found to be associated with the development and poorer survival outcomes of GC. Furthermore, the expression of BNIP3/DAPK1 exhibited an inverse relationship with their DNA methylation levels and demonstrated a positive correlation with immune cell infiltration, as well as the IC50 values of 5-Fluorouracil and Cisplatin in GC tissues. Increased infiltration of macrophages in the high-expression groups was observed to be linked to unfavorable GC survival. In the case-control and follow-up studies, lower methylation levels of BNIP3 and DAPK1 were identified in the peripheral leukocytes of GC patients compared to healthy controls. Hypomethylation was also associated with more aggressive subtypes, diminished chemotherapy efficacy, and poorer survival outcomes in GC. CONCLUSION The DNA methylation of BNIP3 and DAPK1 in peripheral blood leukocytes holds promise as a novel non-invasive biomarker for predicting the occurrence of GC, chemotherapy efficacy, and prognosis assessment.
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Affiliation(s)
- Fang Wang
- Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
| | - Dingtao Hu
- Clinical Cancer Institute, Center for Translational Medicine, Naval Medical University, Shanghai 2004332, China
| | - Xiaoqi Lou
- Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yuhua Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Linlin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Tingyu Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Ziye Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Nana Meng
- Department of Quality Management Office, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yanfeng Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
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Giannini LAA, Boers RG, van der Ende EL, Poos JM, Jiskoot LC, Boers JB, van IJcken WFJ, Dopper EG, Pijnenburg YAL, Seelaar H, Meeter LH, van Rooij JGJ, Scheper W, Gribnau J, van Swieten JC. Distinctive cell-free DNA methylation characterizes presymptomatic genetic frontotemporal dementia. Ann Clin Transl Neurol 2024; 11:744-756. [PMID: 38481040 DOI: 10.1002/acn3.51997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/01/2023] [Accepted: 12/27/2023] [Indexed: 03/27/2024] Open
Abstract
OBJECTIVE Methylation of plasma cell-free DNA (cfDNA) has potential as a marker of brain damage in neurodegenerative diseases such as frontotemporal dementia (FTD). Here, we study methylation of cfDNA in presymptomatic and symptomatic carriers of genetic FTD pathogenic variants, next to healthy controls. METHODS cfDNA was isolated from cross-sectional plasma of 10 presymptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), 10 symptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), and 9 healthy controls. Genome-wide methylation of cfDNA was determined using a high-resolution sequencing technique (MeD-seq). Cumulative scores based on the identified differentially methylated regions (DMRs) were estimated for presymptomatic carriers (vs. controls and symptomatic carriers), and reevaluated in a validation cohort (8 presymptomatic: 3 C9orf72, 3 GRN, and 2 MAPT; 26 symptomatic: 7 C9orf72, 6 GRN, 12 MAPT, and 1 TARDBP; 13 noncarriers from genetic FTD families). RESULTS Presymptomatic carriers showed a distinctive methylation profile compared to healthy controls and symptomatic carriers. Cumulative DMR scores in presymptomatic carriers enabled to significantly differentiate presymptomatic carriers from healthy controls (p < 0.001) and symptomatic carriers (p < 0.001). In the validation cohort, these scores differentiated presymptomatic carriers from symptomatic carriers (p ≤ 0.007) only. Transcription-start-site methylation in presymptomatic carriers, generally associated with gene downregulation, was enriched for genes involved in ubiquitin-dependent processes, while gene body methylation, generally associated with gene upregulation, was enriched for genes involved in neuronal cell processes. INTERPRETATION A distinctive methylation profile of cfDNA characterizes the presymptomatic stage of genetic FTD, and could reflect neuronal death in this stage.
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Affiliation(s)
- Lucia A A Giannini
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ruben G Boers
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Emma L van der Ende
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jackie M Poos
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lize C Jiskoot
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joachim B Boers
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Wilfred F J van IJcken
- Erasmus Center for Biomics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Elise G Dopper
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit, Amsterdam UMC location Vumc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Harro Seelaar
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lieke H Meeter
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jeroen G J van Rooij
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Wiep Scheper
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Human Genetics, Vrije Universiteit, Amsterdam UMC location Vumc, Amsterdam, The Netherlands
| | - Joost Gribnau
- Department of Developmental Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, The Netherlands
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Zillich L, Cetin M, Hummel EM, Poisel E, Fries GR, Frank J, Streit F, Foo JC, Sirignano L, Friske MM, Lenz B, Hoffmann S, Adorjan K, Kiefer F, Bakalkin G, Hansson AC, Lohoff FW, Kärkkäinen O, Kok E, Karhunen PJ, Sutherland GT, Walss-Bass C, Spanagel R, Rietschel M, Moser DA, Witt SH. Biological aging markers in blood and brain tissue indicate age acceleration in alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:250-259. [PMID: 38276909 PMCID: PMC10922212 DOI: 10.1111/acer.15241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 11/30/2023] [Accepted: 12/05/2023] [Indexed: 01/27/2024]
Abstract
BACKGROUND Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation-related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken. METHODS As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63-94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates. RESULTS The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain. CONCLUSIONS The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain.
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Affiliation(s)
- Lea Zillich
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Metin Cetin
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Elisabeth M. Hummel
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, Germany
| | - Eric Poisel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gabriel R. Fries
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jerome C. Foo
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marion M. Friske
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Bernd Lenz
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabine Hoffmann
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Kristina Adorjan
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Falk Kiefer
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Georgy Bakalkin
- Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Anita C. Hansson
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Falk W. Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA
| | - Olli Kärkkäinen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Eloise Kok
- Department of Pathology, University of Helsinki, Helsinki, Finland and HUS Diagnostic Center, Helsinki University Hospital, Helsinki, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pekka J. Karhunen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories Ltd., Pirkanmaa Hospital District, and Finnish Cardiovascular Research Centre Tampere, Tampere, Finland
| | - Greg T Sutherland
- Charles Perkins Centre and School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - Consuelo Walss-Bass
- Louis A. Faillace Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Rainer Spanagel
- Institute of Psychopharmacology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dirk A. Moser
- Department of Genetic Psychology, Faculty of Psychology, Ruhr Universität Bochum, Bochum, Germany
| | - Stephanie H. Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Center for Innovative Psychiatric and Psychotherapeutic Research, Biobank, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Peterson CR, Scott CB, Ghaffari R, Dixon G, Matz MV. Mixed Patterns of Intergenerational DNA Methylation Inheritance in Acropora. Mol Biol Evol 2024; 41:msae008. [PMID: 38243377 PMCID: PMC11079325 DOI: 10.1093/molbev/msae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 12/29/2023] [Accepted: 01/04/2024] [Indexed: 01/21/2024] Open
Abstract
For sessile organisms at high risk from climate change, phenotypic plasticity can be critical to rapid acclimation. Epigenetic markers like DNA methylation are hypothesized as mediators of plasticity; methylation is associated with the regulation of gene expression, can change in response to ecological cues, and is a proposed basis for the inheritance of acquired traits. Within reef-building corals, gene-body methylation (gbM) can change in response to ecological stressors. If coral DNA methylation is transmissible across generations, this could potentially facilitate rapid acclimation to environmental change. We investigated methylation heritability in Acropora, a stony reef-building coral. Two Acropora millepora and two Acropora selago adults were crossed, producing eight offspring crosses (four hybrid, two of each species). We used whole-genome bisulfite sequencing to identify methylated loci and allele-specific alignments to quantify per-locus inheritance. If methylation is heritable, differential methylation (DM) between the parents should equal DM between paired offspring alleles at a given locus. We found a mixture of heritable and nonheritable loci, with heritable portions ranging from 44% to 90% among crosses. gBM was more heritable than intergenic methylation, and most loci had a consistent degree of heritability between crosses (i.e. the deviation between parental and offspring DM were of similar magnitude and direction). Our results provide evidence that coral methylation can be inherited but that heritability is heterogenous throughout the genome. Future investigations into this heterogeneity and its phenotypic implications will be important to understanding the potential capability of intergenerational environmental acclimation in reef building corals.
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Affiliation(s)
| | - Carly B Scott
- Integrative Biology, The University of Texas at Austin, Austin, TX, USA
| | - Rashin Ghaffari
- Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA
| | - Groves Dixon
- Institute for Cell and Molecular Biology, University of Texas at Austin, Austin, TX, USA
| | - Mikhail V Matz
- Integrative Biology, The University of Texas at Austin, Austin, TX, USA
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Klauschen F, Dippel J, Keyl P, Jurmeister P, Bockmayr M, Mock A, Buchstab O, Alber M, Ruff L, Montavon G, Müller KR. Toward Explainable Artificial Intelligence for Precision Pathology. ANNUAL REVIEW OF PATHOLOGY 2024; 19:541-570. [PMID: 37871132 DOI: 10.1146/annurev-pathmechdis-051222-113147] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The rapid development of precision medicine in recent years has started to challenge diagnostic pathology with respect to its ability to analyze histological images and increasingly large molecular profiling data in a quantitative, integrative, and standardized way. Artificial intelligence (AI) and, more precisely, deep learning technologies have recently demonstrated the potential to facilitate complex data analysis tasks, including clinical, histological, and molecular data for disease classification; tissue biomarker quantification; and clinical outcome prediction. This review provides a general introduction to AI and describes recent developments with a focus on applications in diagnostic pathology and beyond. We explain limitations including the black-box character of conventional AI and describe solutions to make machine learning decisions more transparent with so-called explainable AI. The purpose of the review is to foster a mutual understanding of both the biomedical and the AI side. To that end, in addition to providing an overview of the relevant foundations in pathology and machine learning, we present worked-through examples for a better practical understanding of what AI can achieve and how it should be done.
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Affiliation(s)
- Frederick Klauschen
- Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany;
- Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany
- German Cancer Consortium, German Cancer Research Center (DKTK/DKFZ), Munich Partner Site, Munich, Germany
| | - Jonas Dippel
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany
- Machine Learning Group, Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany;
| | - Philipp Keyl
- Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany;
| | - Philipp Jurmeister
- Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany;
- German Cancer Consortium, German Cancer Research Center (DKTK/DKFZ), Munich Partner Site, Munich, Germany
| | - Michael Bockmayr
- Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Research Institute Children's Cancer Center Hamburg, Hamburg, Germany
| | - Andreas Mock
- Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany;
- German Cancer Consortium, German Cancer Research Center (DKTK/DKFZ), Munich Partner Site, Munich, Germany
| | - Oliver Buchstab
- Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany;
| | - Maximilian Alber
- Institute of Pathology, Charité Universitätsmedizin Berlin, Berlin, Germany
- Aignostics, Berlin, Germany
| | | | - Grégoire Montavon
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany
- Machine Learning Group, Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany;
- Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
| | - Klaus-Robert Müller
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany
- Machine Learning Group, Department of Electrical Engineering and Computer Science, Technische Universität Berlin, Berlin, Germany;
- Department of Artificial Intelligence, Korea University, Seoul, Korea
- Max Planck Institute for Informatics, Saarbrücken, Germany
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Carreras-Gallo N, Dwaraka VB, Jima DD, Skaar DA, Mendez TL, Planchart A, Zhou W, Jirtle RL, Smith R, Hoyo C. Creation and Validation of the First Infinium DNA Methylation Array for the Human Imprintome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575646. [PMID: 38293193 PMCID: PMC10827131 DOI: 10.1101/2024.01.15.575646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Background Differentially methylated imprint control regions (ICRs) regulate the monoallelic expression of imprinted genes. Their epigenetic dysregulation by environmental exposures throughout life results in the formation of common chronic diseases. Unfortunately, existing Infinium methylation arrays lack the ability to profile these regions adequately. Whole genome bisulfite sequencing (WGBS) is the unique method able to profile these regions, but it is very expensive and it requires not only a high coverage but it is also computationally intensive to assess those regions. Findings To address this deficiency, we developed a custom methylation array containing 22,819 probes. Among them, 9,757 probes map to 1,088 out of the 1,488 candidate ICRs recently described. To assess the performance of the array, we created matched samples processed with the Human Imprintome array and WGBS, which is the current standard method for assessing the methylation of the Human Imprintome. We compared the methylation levels from the shared CpG sites and obtained a mean R 2 = 0.569. We also created matched samples processed with the Human Imprintome array and the Infinium Methylation EPIC v2 array and obtained a mean R 2 = 0.796. Furthermore, replication experiments demonstrated high reliability (ICC: 0.799-0.945). Conclusions Our custom array will be useful for replicable and accurate assessment, mechanistic insight, and targeted investigation of ICRs. This tool should accelerate the discovery of ICRs associated with a wide range of diseases and exposures, and advance our understanding of genomic imprinting and its relevance in development and disease formation throughout the life course.
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Yu X, Yu K, Chen B, Liao Z, Liang J, Qin Z, Gao X. Metabolic and immune costs balance during natural acclimation of corals in fluctuating environments. MARINE ENVIRONMENTAL RESEARCH 2024; 193:106284. [PMID: 38048660 DOI: 10.1016/j.marenvres.2023.106284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/06/2023]
Abstract
Epigenetic modifications based on DNA methylation can rapidly improve the potential of corals to adapt to environmental pressures by increasing their phenotypic plasticity, a factor important for scleractinian corals to adapt to future global warming. However, the extent to which corals develop similar adaptive mechanisms and their specific adaptation processes remain unclear. Here, to reveal the regulatory mechanism by which DNA methylation improves thermal tolerance in Pocillopora damicornis under fluctuating environments, we analyzed genome-wide DNA methylation signatures in P. damicornis and compared the differences in the methylation and transcriptional responses of P. damicornis from fluctuating and stable environments using whole-genome bisulfite sequencing and nanopore-based RNA sequencingtranscriptome sequencing. We discovered low methylation levels in P. damicornis (average methylation 4.14%), with CpG accounting for 74.88%, CHH for 13.27%, and CHG for 11.85% of this methylation. However, methylation levels did not change between coral samples from the fluctuating and stable environments. The varied methylation levels in different regions of the gene revealed that the overall methylation level of the gene body was relatively high and showed a bimodal methylation pattern. Methylation occurs primarily in exons rather than introns within the gene body In P. damicornis, there was only a weak correlation between methylation and transcriptional changes at the individual gene level, and the methylation and gene expression levels generally exhibited a bell-shaped relationship, which we speculate may be due to the specificity of cnidarian species. Correlation analysis between methylation levels and the transcriptome revealed that the highest proportion of the top 20 enriched KEGG pathways was related to immunity. Additionally, P. damicornis collected from a high-temperature pool had a lower metabolic rate than those collected from a low-temperature pool. We hypothesize that the dynamic balance of energy-expenditure costs between immunity and metabolism is an important strategy for increasing P. damicornis tolerance. The fluctuating environment of high-temperature pools may increase the heat tolerance in corals by increasing their immunity and thus lowering their metabolism.
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Affiliation(s)
- Xiaopeng Yu
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China
| | - Kefu Yu
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China; Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, 511458, China.
| | - Biao Chen
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China
| | - Zhiheng Liao
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China
| | - Jiayuan Liang
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China
| | - Zhenjun Qin
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea, Coral Reef Research Center of China, School of Marine Sciences, Guangxi University, Nanning, China
| | - Xu Gao
- Guangxi University of Chinese Medicine, Nanning, Guangxi, China
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Ho PJ, Khng AJ, Tan BKT, Lim GH, Tan SM, Tan VKM, Tan RSYC, Lim EH, Iau PTC, Chew YJ, Lim YY, Hartman M, Tan EY, Li J. Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway. Breast Cancer Res 2023; 25:136. [PMID: 37932858 PMCID: PMC10626732 DOI: 10.1186/s13058-023-01730-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 10/15/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Exposure to cytotoxic chemotherapy treatment may alter DNA methylation (DNAm) in breast cancer patients. METHODS We performed DNAm analysis in 125 breast cancer patients with blood drawn before and after chemotherapy, using the Illumina MethylationEPIC array. DNAm changes of 588,798 individual CpGs (including 41,207 promoter regions) were evaluated using linear regression models adjusted for monocyte proportion. Gene set enrichment analyses (GSEA) were conducted to identify key Gene Ontology (GO) biological processes or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with chemotherapy. Results were validated in a separate cohort of breast cancer patients who were treated (n = 1273) and not treated (n = 872) by chemotherapy (1808 blood, 337 saliva). RESULTS A total of 141 differentially methylated CpGs and 11 promoters were significantly associated with chemotherapy after multiple testing corrections in both the paired sample and single time point analyses. GSEA of promoter regions (pre-ranked by test statistics) identified six suppressed biological processes (p < 4.67e-8) related to sensory perception and detection of chemical stimuli, including smell perception (GO:0007606, GO:0007608, GO:0009593, GO:0050906, GO:0050907, and GO:0050911). The same six biological processes were significantly suppressed in the validation dataset (p < 9.02e-14). The KEGG pathway olfactory transduction (hsa04740) was also found to be significantly suppressed (ppaired-samples = 1.72e-9, psingle-timepoint-blood = 2.03e-15 and psingle-timepoint-saliva = 7.52e-56). CONCLUSION The enrichment of imprinted genes within biological processes and pathways suggests a biological mechanism by which chemotherapy could affect the perception of smell.
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Affiliation(s)
- Peh Joo Ho
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Alexis Jiaying Khng
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore
| | - Benita Kiat-Tee Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Republic of Singapore
- Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
- Department of General Surgery, Sengkang General Hospital, Singapore, Republic of Singapore
| | - Geok Hoon Lim
- KK Breast Department, KK Women's and Children's Hospital, Singapore, 229899, Republic of Singapore
| | - Su-Ming Tan
- Division of Breast Surgery, Changi General Hospital, Singapore, Republic of Singapore
| | - Veronique Kiak Mien Tan
- Department of Breast Surgery, Singapore General Hospital, Singapore, Republic of Singapore
- Division of Surgery and Surgical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
| | - Ryan Shea Ying Cong Tan
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
- Oncology Academic Programme, Duke-NUS Medical School, Singapore, Republic of Singapore
| | - Elaine Hsuen Lim
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Republic of Singapore
| | - Philip Tsau-Choong Iau
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
- Department of General Surgery, Ng Teng Fong General Hospital, 1 Jurong East St 21, Singapore, 609606, Republic of Singapore
| | - Ying Jia Chew
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
- Department of General Surgery, Ng Teng Fong General Hospital, 1 Jurong East St 21, Singapore, 609606, Republic of Singapore
| | - Yi Ying Lim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore
- Department of Surgery, University Surgical Cluster, National University Health System, Singapore, 119228, Singapore
| | - Ern Yu Tan
- Department of General Surgery, Tan Tock Seng Hospital, Singapore, 308433, Republic of Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore
| | - Jingmei Li
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, 138672, Republic of Singapore.
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Republic of Singapore.
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20
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Yu D, Zhang J, Gao N, Huo Y, Li W, Wang T, Zhang X, Simayijiang H, Yan J. Rapid and visual detection of specific bacteria for saliva and vaginal fluid identification with the lateral flow dipstick strategy. Int J Legal Med 2023; 137:1853-1863. [PMID: 37358650 DOI: 10.1007/s00414-023-03051-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 06/19/2023] [Indexed: 06/27/2023]
Abstract
Identification of body fluids is critical for crime scene reconstruction, and a source of investigation source of investigative leads. In recent years, microbial DNA analysis using sequencing and quantitative real-time polymerase chain reaction have been used to identify body fluids. However, these techniques are time-consuming, expensive, and require complex workflows. In this study, a new method for simultaneous detection of Streptococcus salivarius and Lactobacillus crispatus using polymerase chain reaction (PCR) in combination with a lateral flow dipstick (LFD) was developed to identify saliva and vaginal fluid in forensic samples. LFD results can be observed with the naked eye within 3 min with a sensitivity of 0.001 ng/µL DNA. The PCR-LFD assay was successfully used to detect S. salivarius and L. crispatus in saliva and vaginal fluid respectively, and showed negative results in blood, semen, nasal fluid, and skin. Moreover, saliva and vaginal fluid were detectable even at an extremely high mixing ratio of sample DNA (1:999). Saliva and vaginal fluid were identified in various mock forensic samples. These results indicate that saliva and vaginal fluid can be effectively detected by identifying S. salivarius and L. crispatus, respectively. Furthermore, we have shown that DNA samples used to identify saliva and vaginal fluid can also provide a complete short tandem repeat (STR) profile when used as source material for forensic STR profiling. In summary, our results suggest that PCR-LFD is a promising assay for rapid, simple, reliable, and efficient identification of body fluids.
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Affiliation(s)
- Daijing Yu
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Jun Zhang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Niu Gao
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Yumei Huo
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Wanting Li
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Tian Wang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Xiaomeng Zhang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Halimureti Simayijiang
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030600, Shanxi, People's Republic of China.
- Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, People's Republic of China.
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21
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Andrews JL, Zalesky A, Nair S, Sullivan RP, Green MJ, Pantelis C, Newell KA, Fernandez F. Genetic and Epigenetic Regulation in Lingo-1: Effects on Cognitive Function and White Matter Microstructure in a Case-Control Study for Schizophrenia. Int J Mol Sci 2023; 24:15624. [PMID: 37958608 PMCID: PMC10648795 DOI: 10.3390/ijms242115624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 10/19/2023] [Accepted: 10/22/2023] [Indexed: 11/15/2023] Open
Abstract
Leucine-rich repeat and immunoglobulin domain-containing protein (Lingo-1) plays a vital role in a large number of neuronal processes underlying learning and memory, which are known to be disrupted in schizophrenia. However, Lingo-1 has never been examined in the context of schizophrenia. The genetic association of a single-nucleotide polymorphism (SNP, rs3144) and methylation (CpG sites) in the Lingo-1 3'-UTR region was examined, with the testing of cognitive dysfunction and white matter (WM) integrity in a schizophrenia case-control cohort (n = 268/group). A large subset of subjects (97 control and 161 schizophrenia subjects) underwent structural magnetic resonance imaging (MRI) brain scans to assess WM integrity. Frequency of the rs3144 minor allele was overrepresented in the schizophrenia population (p = 0.03), with an odds ratio of 1.39 (95% CI 1.016-1.901). CpG sites surrounding rs3144 were hypermethylated in the control population (p = 0.032) compared to the schizophrenia group. rs3144 genotype was predictive of membership to a subclass of schizophrenia subjects with generalized cognitive deficits (p < 0.05), in addition to having associations with WM integrity (p = 0.018). This is the first study reporting a potential implication of genetic and epigenetic risk factors in Lingo-1 in schizophrenia. Both of these genetic and epigenetic alterations may also have associations with cognitive dysfunction and WM integrity in the context of the schizophrenia pathophysiology.
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Affiliation(s)
- Jessica L. Andrews
- School of Medical, Indigenous and Health Sciences, and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW 2522, Australia (K.A.N.)
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, VIC 3053, Australia; (A.Z.); (C.P.)
| | - Shalima Nair
- Epigenetics Research Program, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia;
| | - Ryan P. Sullivan
- ARC Centre of Excellence for Electromaterials Science, Intelligent Polymer Research Institute, AIIM Facility, University of Wollongong, Wollongong, NSW 2522, Australia;
| | - Melissa J. Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, UNSW Sydney, Sydney, NSW 2052, Australia;
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, VIC 3053, Australia; (A.Z.); (C.P.)
| | - Kelly A. Newell
- School of Medical, Indigenous and Health Sciences, and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW 2522, Australia (K.A.N.)
| | - Francesca Fernandez
- School of Medical, Indigenous and Health Sciences, and Molecular Horizons, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW 2522, Australia (K.A.N.)
- School of Behavioural and Health Sciences, Faculty of Heath Sciences, Australian Catholic University, Banyo, QLD 4014, Australia
- Healthy Brain and Mind Research Centre, Australian Catholic University, Fitzroy, VIC 3065, Australia
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22
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Budeus B, Unger K, Hess J, Sentek H, Klein D. Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts. Front Immunol 2023; 14:1270493. [PMID: 37822926 PMCID: PMC10562561 DOI: 10.3389/fimmu.2023.1270493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/30/2023] [Indexed: 10/13/2023] Open
Abstract
Introduction Mesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organ-specific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly- at least concerning the classical marker genes- indistinguishable from similar lineage cells, particularly fibroblasts. Methods Here we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action. Results We identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential. Discussion Conclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential.
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Affiliation(s)
- Bettina Budeus
- Institute for Cell Biology (Cancer Research), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Kristian Unger
- Research Unit Radiation Cytogenetics, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
- Clinical Cooperation Group Personalized Radiotherapy in Head and Neck Cancer, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
| | - Julia Hess
- Research Unit Radiation Cytogenetics, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
- Clinical Cooperation Group Personalized Radiotherapy in Head and Neck Cancer, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Neuherberg, Germany
| | - Hanna Sentek
- Institute for Cell Biology (Cancer Research), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Diana Klein
- Institute for Cell Biology (Cancer Research), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
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23
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Zhang S, He S, Zhu X, Wang Y, Xie Q, Song X, Xu C, Wang W, Xing L, Xia C, Wang Q, Li W, Zhang X, Yu J, Ma S, Shi J, Gu H. DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues. Nat Commun 2023; 14:5686. [PMID: 37709764 PMCID: PMC10502058 DOI: 10.1038/s41467-023-41015-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 08/18/2023] [Indexed: 09/16/2023] Open
Abstract
Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).
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Affiliation(s)
- Shirong Zhang
- Translational Medicine Research Center, Hangzhou First People's Hospital, 310006, Hangzhou, Zhejiang Province, China
- Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Hangzhou First People's Hospital, 310006, Hangzhou, Zhejiang Province, China
| | - Shutao He
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, 200031, Shanghai, China
- Institute of Biotechnology and Health, Beijing Academy of Science and Technology, 100089, Beijing, China
| | - Xin Zhu
- Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, 310022, Hangzhou, Zhejiang Province, China
| | - Yunfei Wang
- Zhejiang ShengTing Biotech Co. Ltd, 310018, Hangzhou, Zhejiang Province, China
| | - Qionghuan Xie
- Zhejiang ShengTing Biotech Co. Ltd, 310018, Hangzhou, Zhejiang Province, China
| | - Xianrang Song
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 250117, Jinan, Shandong Province, China
| | - Chunwei Xu
- Department of Respiratory Medicine, Jinling Hospital, Nanjing University School of Medicine, 210002, Nanjing, Jiangshu Province, China
| | - Wenxian Wang
- Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, 310022, Hangzhou, Zhejiang Province, China
| | - Ligang Xing
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 250117, Jinan, Shandong Province, China
| | - Chengqing Xia
- Zhejiang ShengTing Biotech Co. Ltd, 310018, Hangzhou, Zhejiang Province, China
| | - Qian Wang
- Department of Respiratory Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, 210029, Nanjing, Jiangshu Province, China
| | - Wenfeng Li
- Department of Medical Oncology, The First Affiliated Hospital of Wenzhou Medical University, 325000, Wenzhou, Zhejiang Province, China
| | - Xiaochen Zhang
- Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, 310006, Hangzhou, Zhejiang Province, China
| | - Jinming Yu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 250117, Jinan, Shandong Province, China
| | - Shenglin Ma
- Translational Medicine Research Center, Hangzhou First People's Hospital, 310006, Hangzhou, Zhejiang Province, China.
- Department of Oncology, Hangzhou Cancer Hospital, 310006, Hangzhou, Zhejiang Province, China.
| | - Jiantao Shi
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, 200031, Shanghai, China.
| | - Hongcang Gu
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, 230031, Hefei, Anhui Province, China.
- Hefei Cancer Hospital, Chinese Academy of Sciences, 230031, Hefei, Anhui Province, China.
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24
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Li S, Zeng W, Ni X, Liu Q, Li W, Stackpole ML, Zhou Y, Gower A, Krysan K, Ahuja P, Lu DS, Raman SS, Hsu W, Aberle DR, Magyar CE, French SW, Han SHB, Garon EB, Agopian VG, Wong WH, Dubinett SM, Zhou XJ. Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring. Proc Natl Acad Sci U S A 2023; 120:e2305236120. [PMID: 37399400 PMCID: PMC10334733 DOI: 10.1073/pnas.2305236120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 05/16/2023] [Indexed: 07/05/2023] Open
Abstract
Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.
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Affiliation(s)
- Shuo Li
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Weihua Zeng
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Xiaohui Ni
- EarlyDiagnostics Inc., Los Angeles, CA90095
| | - Qiao Liu
- Department of Statistics, Stanford University, Stanford, CA94305
| | - Wenyuan Li
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Institute for Quantitative & Computational Biosciences, University of California at Los Angeles, Los Angeles, CA90095
| | - Mary L. Stackpole
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- EarlyDiagnostics Inc., Los Angeles, CA90095
| | - Yonggang Zhou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - Arjan Gower
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Kostyantyn Krysan
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Veterans Administration (VA) Greater Los Angeles Health Care System, Los Angeles, CA90073
| | - Preeti Ahuja
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
| | - David S. Lu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Steven S. Raman
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Surgery, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - William Hsu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Denise R. Aberle
- Department of Radiological Sciences, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Department of Bioengineering, University of California, Los Angeles, CA90095
| | - Clara E. Magyar
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Samuel W. French
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Steven-Huy B. Han
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Edward B. Garon
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
| | - Vatche G. Agopian
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Surgery, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Wing Hung Wong
- Department of Statistics, Stanford University, Stanford, CA94305
- Department of Biomedical Data Science, Stanford University, Stanford, CA94305
| | - Steven M. Dubinett
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Department of Medicine, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
- Veterans Administration (VA) Greater Los Angeles Health Care System, Los Angeles, CA90073
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA90095
| | - Xianghong Jasmine Zhou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA90095
- Institute for Quantitative & Computational Biosciences, University of California at Los Angeles, Los Angeles, CA90095
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles, Los Angeles, CA90095
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25
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Lukacova E, Burjanivova T, Podlesniy P, Grendar M, Turyova E, Kasubova I, Laca L, Mikolajcik P, Kudelova E, Vanochova A, Miklusica J, Mersakova S, Lasabova Z. Hypermethylated GRIA4, a potential biomarker for an early non-invasive detection of metastasis of clinically known colorectal cancer. Front Oncol 2023; 13:1205791. [PMID: 37476382 PMCID: PMC10354553 DOI: 10.3389/fonc.2023.1205791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 06/12/2023] [Indexed: 07/22/2023] Open
Abstract
Introduction Colorectal cancer (CRC) can develop through several dysregulated molecular pathways, including the serrated pathway, characterized by CpG island methylator (CIMP) phenotype. Although the tumor tissue is a commonly tested material, sample types such as stool or plasma, bring a new, non-invasive approach. Several cancer-related methylated genes have been identified in CRC patients, including gene GRIA4, showing promising diagnostic potential. The aim of our study was to develop a sensitive droplet digital PCR (ddPCR) assay to examine GRIA4 hypermethylation status in CRC patients and evaluate its diagnostic potential in tissue and liquid biopsy samples. Methods In total, 23 patients participated in this study, 7 patients with primary CRC and 16 patients with liver metastasis of clinically known CRC. We obtained tumor and non-tumor tissues (N=17), blood samples pre- and post-surgery (N=22), and blood of five volunteers without a personal cancer history. We have developed and optimized a ddPCR assay for GRIA4 hypermethylation detection, from tissue and plasma samples. Results We detected significantly increased GRIA4 methylation in tumor tissues compared to their adjacent non-tumor tissue, p<0.0001. Receiver operating characteristic (ROC) analysis defined cutoff values to separate primary tumors and metastases from non-tumor colon/rectum, specifically 36.85% for primary tumors and 34.81% for metastases. All primary tumors were above this threshold. When comparing the methylation levels of metastatic vs. non-tumor tissue, a smaller increase was observed in liver metastasis versus colon tissue (3.6× gain; p=0.001), then in liver metastasis versus adjacent liver tissue (17.4× gain; p<0.0001). On average, GRIA4 hypermethylation in primary tumor plasma was 2.8-fold higher (p=0.39), and in metastatic plasma, 16.4-fold higher (p=0.0011) compared to healthy individuals. Hypermethylation in metastatic plasma was on average 5.9 times higher (p=0.051) than in primary tumor plasma. After tumor removal surgery, average hypermethylation decrease in plasma was 1.6× for primary (p=0.037) and 4.5× for metastatic patients (p=0.023). Discussion Based on our data, it can be inferred that GRIA4 serves as a tissue specific biomarker for the colon/rectum tissue, thus is suitable for cancer classification. This biomarker showed the potential to be an attractive target for early non-invasive detection of metastases of clinically known CRC, although additional analysis has to be performed.
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Affiliation(s)
- Eva Lukacova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - Tatiana Burjanivova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - Petar Podlesniy
- Centro Investigacion Biomedica en Red Enfermedades Neurodegenerativas (CiberNed), Madrid, Spain
| | - Marian Grendar
- Laboratory of Bioinformatics and Biostatistics, Biomedical Center Martin JFM CU, Commenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - Eva Turyova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - Ivana Kasubova
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Ludovit Laca
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Peter Mikolajcik
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Eva Kudelova
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Andrea Vanochova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
| | - Juraj Miklusica
- Clinic of Surgery and Transplant Center, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Sandra Mersakova
- Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia
| | - Zora Lasabova
- Department of Molecular Biology and Genomics, Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin (JFM CU), Martin, Slovakia
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26
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Zhang L, Han Z, He H, Zhang X, Zhang M, Li B, Wu Q. Meg8-DMR as the Secondary Regulatory Region Regulates the Expression of MicroRNAs While It Does Not Affect Embryonic Development in Mice. Genes (Basel) 2023; 14:1264. [PMID: 37372444 DOI: 10.3390/genes14061264] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 06/29/2023] Open
Abstract
Meg8-DMR is the first maternal methylated DMR to be discovered in the imprinted Dlk1-Dio3 domain. The deletion of Meg8-DMR enhances the migration and invasion of MLTC-1 depending on the CTCF binding sites. However, the biological function of Meg8-DMR during mouse development remains unknown. In this study, a CRISPR/Cas9 system was used to generate 434 bp genomic deletions of Meg8-DMR in mice. High-throughput and bioinformatics profiling revealed that Meg8-DMR is involved in the regulation of microRNA: when the deletion was inherited from the mother (Mat-KO), the expression of microRNA was unchanged. However, when the deletion occurred from the father (Pat-KO) and homozygous (Homo-KO), the expression was upregulated. Then, differentially expressed microRNAs (DEGs) were identified between WT with Pat-KO, Mat-KO, and Homo-KO, respectively. Subsequently, these DEGs were subjected to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) term enrichment analysis to explore the functional roles of these genes. In total, 502, 128, and 165 DEGs were determined. GO analysis showed that these DEGs were mainly enriched in axonogenesis in Pat-KO and Home-KO, while forebrain development was enriched in Mat-KO. Finally, the methylation levels of IG-DMR, Gtl2-DMR, and Meg8-DMR, and the imprinting status of Dlk1, Gtl2, and Rian were not affected. These findings suggest that Meg8-DMR, as a secondary regulatory region, could regulate the expression of microRNAs while not affecting the normal embryonic development of mice.
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Affiliation(s)
- Liang Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Zhengbin Han
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Hongjuan He
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Ximeijia Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Mengyan Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Boran Li
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Qiong Wu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China
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27
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Hu Y, Yuan S, Du X, Liu J, Zhou W, Wei F. Comparative analysis reveals epigenomic evolution related to species traits and genomic imprinting in mammals. Innovation (N Y) 2023; 4:100434. [PMID: 37215528 PMCID: PMC10196708 DOI: 10.1016/j.xinn.2023.100434] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 04/25/2023] [Indexed: 05/24/2023] Open
Abstract
DNA methylation is an epigenetic modification that plays a crucial role in various regulatory processes, including gene expression regulation, transposable element repression, and genomic imprinting. However, most studies on DNA methylation have been conducted in humans and other model species, whereas the dynamics of DNA methylation across mammals remain poorly explored, limiting our understanding of epigenomic evolution in mammals and the evolutionary impacts of conserved and lineage-specific DNA methylation. Here, we generated and gathered comparative epigenomic data from 13 mammalian species, including two marsupial species, to demonstrate that DNA methylation plays critical roles in several aspects of gene evolution and species trait evolution. We found that the species-specific DNA methylation of promoters and noncoding elements correlates with species-specific traits such as body patterning, indicating that DNA methylation might help establish or maintain interspecies differences in gene regulation that shape phenotypes. For a broader view, we investigated the evolutionary histories of 88 known imprinting control regions across mammals to identify their evolutionary origins. By analyzing the features of known and newly identified potential imprints in all studied mammals, we found that genomic imprinting may function in embryonic development through the binding of specific transcription factors. Our findings show that DNA methylation and the complex interaction between the genome and epigenome have a significant impact on mammalian evolution, suggesting that evolutionary epigenomics should be incorporated to develop a unified evolutionary theory.
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Affiliation(s)
- Yisi Hu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
| | - Shenli Yuan
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xin Du
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jiang Liu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China
| | - Wenliang Zhou
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
| | - Fuwen Wei
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Evolution and Conservation Biology, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
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28
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Mongelli A, Panunzi S, Nesta M, Gottardi Zamperla M, Atlante S, Barbi V, Mongiardini V, Ferraro F, De Martino S, Cis L, Re A, Maltese S, Bachetti T, La Rovere MT, Martelli F, Pesce M, Nanni S, Massetti M, Pontecorvi A, Farsetti A, Gaetano C. Distinguishable DNA methylation defines a cardiac-specific epigenetic clock. Clin Epigenetics 2023; 15:53. [PMID: 36991505 PMCID: PMC10053964 DOI: 10.1186/s13148-023-01467-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Accepted: 03/18/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND The present study investigates whether epigenetic differences emerge in the heart of patients undergoing cardiac surgery for an aortic valvular replacement (AVR) or coronary artery bypass graft (CABG). An algorithm is also established to determine how the pathophysiological condition might influence the human biological cardiac age. RESULTS Blood samples and cardiac auricles were collected from patients who underwent cardiac procedures: 94 AVR and 289 CABG. The CpGs from three independent blood-derived biological clocks were selected to design a new blood- and the first cardiac-specific clocks. Specifically, 31 CpGs from six age-related genes, ELOVL2, EDARADD, ITGA2B, ASPA, PDE4C, and FHL2, were used to construct the tissue-tailored clocks. The best-fitting variables were combined to define new cardiac- and blood-tailored clocks validated through neural network analysis and elastic regression. In addition, telomere length (TL) was measured by qPCR. These new methods revealed a similarity between chronological and biological age in the blood and heart; the average TL was significantly higher in the heart than in the blood. In addition, the cardiac clock discriminated well between AVR and CABG and was sensitive to cardiovascular risk factors such as obesity and smoking. Moreover, the cardiac-specific clock identified an AVR patient's subgroup whose accelerated bioage correlated with the altered ventricular parameters, including left ventricular diastolic and systolic volume. CONCLUSION This study reports on applying a method to evaluate the cardiac biological age revealing epigenetic features that separate subgroups of AVR and CABG.
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Affiliation(s)
- A Mongelli
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy
- Center for Translational and Experimental Cardiology (CTEC), University of Zurich, 8952, Schlieren, Switzerland
| | - S Panunzi
- National Research Council (CNR)-IASI, 00185, Rome, Italy
| | - M Nesta
- Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
| | - M Gottardi Zamperla
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy
| | - S Atlante
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy
| | - V Barbi
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy
| | - V Mongiardini
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy
- Molecular Medicine, Istituto Italiano di Tecnologia, Genoa, Italy
| | - F Ferraro
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - S De Martino
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - L Cis
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - A Re
- National Research Council (CNR)-IASI, 00185, Rome, Italy
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - S Maltese
- National Research Council (CNR)-IRIB, 90146, Palermo, Italy
| | - T Bachetti
- Direzione Scientifica Centrale ICS Maugeri IRCCS, Pavia, Italy
| | - M T La Rovere
- Dipartimento di Cardiologia ICS Maugeri and Direzione Scientifica ICS Maugeri Montescano IRCCS, Pavia, Italy
| | - F Martelli
- Molecular Cardiology Laboratory, IRCCS Policlinico San Donato, San Donato Milanese, Milan, Italy
| | - M Pesce
- Unità di Ingegneria Tissutale Cardiovascolare, Centro Cardiologico Monzino IRCCS, 20138, Milan, Italy
| | - S Nanni
- Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - M Massetti
- Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - A Pontecorvi
- Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - A Farsetti
- National Research Council (CNR)-IASI, 00185, Rome, Italy.
| | - C Gaetano
- Laboratorio di Epigenetica, Istituti Clinici Scientifici (ICS) Maugeri IRCCS, 27100, Pavia, Italy.
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Brito-Rocha T, Constâncio V, Henrique R, Jerónimo C. Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests. Cells 2023; 12:cells12060935. [PMID: 36980276 PMCID: PMC10047029 DOI: 10.3390/cells12060935] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/14/2023] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
Cancer remains a leading cause of death worldwide, partly owing to late detection which entails limited and often ineffective therapeutic options. Most cancers lack validated screening procedures, and the ones available disclose several drawbacks, leading to low patient compliance and unnecessary workups, adding up the costs to healthcare systems. Hence, there is a great need for innovative, accurate, and minimally invasive tools for early cancer detection. In recent years, multi-cancer early detection (MCED) tests emerged as a promising screening tool, combining molecular analysis of tumor-related markers present in body fluids with artificial intelligence to simultaneously detect a variety of cancers and further discriminate the underlying cancer type. Herein, we aim to provide a highlight of the variety of strategies currently under development concerning MCED, as well as the major factors which are preventing clinical implementation. Although MCED tests depict great potential for clinical application, large-scale clinical validation studies are still lacking.
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Affiliation(s)
- Tiago Brito-Rocha
- Cancer Biology and Epigenetics Group, Research Center (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Center Raquel Seruca (P.CCC), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Master Program in Oncology, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-513 Porto, Portugal
| | - Vera Constâncio
- Cancer Biology and Epigenetics Group, Research Center (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Center Raquel Seruca (P.CCC), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Doctoral Program in Biomedical Sciences, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-513 Porto, Portugal
| | - Rui Henrique
- Cancer Biology and Epigenetics Group, Research Center (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Center Raquel Seruca (P.CCC), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Department of Pathology, Portuguese Oncology Institute of Porto (IPO-Porto), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Department of Pathology and Molecular Immunology, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-513 Porto, Portugal
| | - Carmen Jerónimo
- Cancer Biology and Epigenetics Group, Research Center (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO-Porto)/Porto Comprehensive Cancer Center Raquel Seruca (P.CCC), Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal
- Department of Pathology and Molecular Immunology, School of Medicine & Biomedical Sciences, University of Porto (ICBAS-UP), Rua Jorge Viterbo Ferreira 228, 4050-513 Porto, Portugal
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Silva R, Glennon K, Metoudi M, Moran B, Salta S, Slattery K, Treacy A, Martin T, Shaw J, Doran P, Lynch L, Jeronimo C, Perry AS, Brennan DJ. Unveiling the epigenomic mechanisms of acquired platinum-resistance in high-grade serous ovarian cancer. Int J Cancer 2023; 153:120-132. [PMID: 36883413 DOI: 10.1002/ijc.34496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 01/19/2023] [Accepted: 02/17/2023] [Indexed: 03/09/2023]
Abstract
Resistance to platinum-based chemotherapy is the major cause of death from high-grade serous ovarian cancer (HGSOC). We hypothesise that detection of specific DNA methylation changes may predict platinum resistance in HGSOC. Using a publicly available "discovery" dataset we examined epigenomic and transcriptomic alterations between primary platinum-sensitive (n = 32) and recurrent acquired drug resistant HGSOC (n = 28) and identified several genes involved in immune and chemoresistance-related pathways. Validation via high-resolution melt analysis of these findings, in cell lines and HGSOC tumours, demonstrated the most consistent changes were observed in three of the genes: APOBEC3A, NKAPL and PDCD1. Plasma samples from an independent HGSOC cohort (n = 17) were analysed using droplet digital PCR. Hypermethylation of NKAPL was detected in 46% and hypomethylation of APOBEC3A in 69% of plasma samples taken from women with relapsed HGSOC (n = 13), with no alterations identified in disease-free patients (n = 4). Following these results, and using a CRISPR-Cas9 approach, we were also able to demonstrate that in vitro NKAPL promoter demethylation increased platinum sensitivity by 15%. Overall, this study demonstrates the importance of aberrant methylation, especially of the NKAPL gene, in acquired platinum resistance in HGSOC.
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Affiliation(s)
- Romina Silva
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
- Systems Biology Ireland, UCD School of Medicine, University College Dublin, Dublin, Ireland
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - Kate Glennon
- UCD Gynaecological Oncology Group, UCD School of Medicine Mater Misericordiae University Hospital, Dublin, Ireland
| | - Michael Metoudi
- Systems Biology Ireland, UCD School of Medicine, University College Dublin, Dublin, Ireland
| | - Bruce Moran
- Department of Pathology, St Vincent's University Hospital, Dublin, Ireland
| | - Sofia Salta
- Cancer Biology & Epigenetics Group, IPO Porto Research Center of IPO Porto (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto /Porto Comprehensive Cancer Centre (Porto.CCC), Porto, Portugal
| | - Karen Slattery
- School of Biochemistry and Immunology, Trinity College Dublin, Dublin, Ireland
| | - Ann Treacy
- Department of Pathology, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Terri Martin
- Clinical Research Centre, UCD School of Medicine, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Jacqui Shaw
- Leicester Cancer Research Centre, University of Leicester, Leicester, UK
| | - Peter Doran
- Clinical Research Centre, UCD School of Medicine, Mater Misericordiae University Hospital, Dublin, Ireland
| | - Lydia Lynch
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Trinity Biomedical Science Institute, Trinity College Dublin, Dublin, Ireland
| | - Carmen Jeronimo
- Cancer Biology & Epigenetics Group, IPO Porto Research Center of IPO Porto (CI-IPOP)/RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto /Porto Comprehensive Cancer Centre (Porto.CCC), Porto, Portugal
- Department of Pathology and Molecular Immunology, Institute of Biomedical Sciences Abel Salazar, University of Porto (ICBAS-UP), Porto, Portugal
| | - Antoinette S Perry
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - Donal J Brennan
- Systems Biology Ireland, UCD School of Medicine, University College Dublin, Dublin, Ireland
- UCD Gynaecological Oncology Group, UCD School of Medicine Mater Misericordiae University Hospital, Dublin, Ireland
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Trangle SS, Rosenberg T, Parnas H, Levy G, Bar E, Marco A, Barak B. In individuals with Williams syndrome, dysregulation of methylation in non-coding regions of neuronal and oligodendrocyte DNA is associated with pathology and cortical development. Mol Psychiatry 2023; 28:1112-1127. [PMID: 36577841 DOI: 10.1038/s41380-022-01921-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 12/03/2022] [Accepted: 12/12/2022] [Indexed: 12/29/2022]
Abstract
Williams syndrome (WS) is a neurodevelopmental disorder caused by a heterozygous micro-deletion in the WS critical region (WSCR) and is characterized by hyper-sociability and neurocognitive abnormalities. Nonetheless, whether and to what extent WSCR deletion leads to epigenetic modifications in the brain and induces pathological outcomes remains largely unknown. By examining DNA methylation in frontal cortex, we revealed genome-wide disruption in the methylome of individuals with WS, as compared to typically developed (TD) controls. Surprisingly, differentially methylated sites were predominantly annotated as introns and intergenic loci and were found to be highly enriched around binding sites for transcription factors that regulate neuronal development, plasticity and cognition. Moreover, by utilizing enhancer-promoter interactome data, we confirmed that most of these loci function as active enhancers in the human brain or as target genes of transcriptional networks associated with myelination, oligodendrocyte (OL) differentiation, cognition and social behavior. Cell type-specific methylation analysis revealed aberrant patterns in the methylation of active enhancers in neurons and OLs, and important neuron-glia interactions that might be impaired in individuals with WS. Finally, comparison of methylation profiles from blood samples of individuals with WS and healthy controls, along with other data collected in this study, identified putative targets of endophenotypes associated with WS, which can be used to define brain-risk loci for WS outside the WSCR locus, as well as for other associated pathologies. In conclusion, our study illuminates the brain methylome landscape of individuals with WS and sheds light on how these aberrations might be involved in social behavior and physiological abnormalities. By extension, these results may lead to better diagnostics and more refined therapeutic targets for WS.
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Affiliation(s)
- Sari Schokoroy Trangle
- The School of Psychological Sciences, Faculty of Social Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Tali Rosenberg
- Neuro-Epigenetics Laboratory, Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, 7610001, Israel
| | - Hadar Parnas
- Neuro-Epigenetics Laboratory, Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, 7610001, Israel
| | - Gilad Levy
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Ela Bar
- The School of Psychological Sciences, Faculty of Social Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel.,The School of Neurobiology, Biochemistry & Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel
| | - Asaf Marco
- Neuro-Epigenetics Laboratory, Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, 7610001, Israel.
| | - Boaz Barak
- The School of Psychological Sciences, Faculty of Social Sciences, Tel Aviv University, Tel Aviv, 6997801, Israel. .,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, 6997801, Israel.
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Eaves LA, Enggasser AE, Camerota M, Gogcu S, Gower WA, Hartwell H, Jackson WM, Jensen E, Joseph RM, Marsit CJ, Roell K, Santos HP, Shenberger JS, Smeester L, Yanni D, Kuban KCK, O'Shea TM, Fry RC. CpG methylation patterns in placenta and neonatal blood are differentially associated with neonatal inflammation. Pediatr Res 2023; 93:1072-1084. [PMID: 35764815 PMCID: PMC10289042 DOI: 10.1038/s41390-022-02150-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/09/2022] [Accepted: 05/26/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND Infants born extremely premature are at increased risk for health complications later in life for which neonatal inflammation may be a contributing biological driver. Placental CpG methylation provides mechanistic information regarding the relationship between prenatal epigenetic programming, prematurity, neonatal inflammation, and later-in-life health. METHODS We contrasted CpG methylation in the placenta and neonatal blood spots in relation to neonatal inflammation in the Extremely Low Gestational Age Newborn (ELGAN) cohort. Neonatal inflammation status was based on the expression of six inflammation-related proteins, assessed as (1) day-one inflammation (DOI) or (2) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 postnatal weeks). Epigenome-wide CpG methylation was assessed in 354 placental samples and 318 neonatal blood samples. RESULTS Placental CpG methylation displayed the strongest association with ISSI (48 CpG sites) but was not associated with DOI. This was in contrast to CpG methylation in blood spots, which was associated with DOI (111 CpG sites) and not with ISSI (one CpG site). CONCLUSIONS Placental CpG methylation was strongly associated with ISSI, a measure of inflammation previously linked to later-in-life cognitive impairment, while day-one neonatal blood methylation was associated with DOI. IMPACT Neonatal inflammation increases the risk of adverse later-life outcomes, especially in infants born extremely preterm. CpG methylation in the placenta and neonatal blood spots were evaluated in relation to neonatal inflammation assessed via circulating proteins as either (i) day-one inflammation (DOI) or (ii) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 weeks). Tissue specificity was observed in epigenetic-inflammatory relationships: placental CpG methylation was associated with ISSI, neonatal blood CpG methylation was associated with DOI. Supporting the placental origins of disease framework, placental epigenetic patterns are associated with a propensity for ISSI in neonates.
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Affiliation(s)
- Lauren A Eaves
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Adam E Enggasser
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marie Camerota
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
| | - Semsa Gogcu
- Division of Neonatology, Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - William A Gower
- Department of Pediatrics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Hadley Hartwell
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wesley M Jackson
- Department of Pediatrics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Elizabeth Jensen
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Carmen J Marsit
- Gangarosa Department of Environmental Health, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Kyle Roell
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hudson P Santos
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- School of Nursing & Health Studies, University of Miami, Miami, FL, USA
| | - Jeffrey S Shenberger
- Division of Neonatology, Department of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Lisa Smeester
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Diana Yanni
- Department of Neonatology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Karl C K Kuban
- Division of Pediatric Neurology, Department of Pediatrics, School of Medicine, Boston University Medical Center, Boston, MA, USA
| | - T Michael O'Shea
- Department of Pediatrics, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Rebecca C Fry
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Institute for Environmental Health Solutions, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Curriculum in Toxicology and Environmental Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Gallardo VJ, Vila-Pueyo M, Pozo-Rosich P. The impact of epigenetic mechanisms in migraine: Current knowledge and future directions. Cephalalgia 2023; 43:3331024221145916. [PMID: 36759209 DOI: 10.1177/03331024221145916] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
BACKGROUND Epigenetic mechanisms, including DNA methylation, microRNAs and histone modifications, may modulate the genetic expression in migraine and its interaction with internal and external factors, such as lifestyle and environmental changes. OBJECTIVE To summarize, contextualize and critically analyze the published literature on the current state of epigenetic mechanisms in migraine in a narrative review. FINDINGS The studies published to date have used different approaches and methodologies to determine the role of epigenetic mechanisms in migraine. Epigenetic changes seem to be involved in migraine and are increasing our knowledge of the disease. CONCLUSIONS Changes in DNA methylation, microRNA expression and histone modifications could be utilized as biomarkers that would be highly valuable for patient stratification, molecular diagnosis, and precision medicine in migraine.
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Affiliation(s)
- Víctor José Gallardo
- Headache and Neurological Pain Research Group, Vall d'Hebron Institute of Research, Universitat Autònoma de Barcelona, Spain
| | - Marta Vila-Pueyo
- Headache and Neurological Pain Research Group, Vall d'Hebron Institute of Research, Universitat Autònoma de Barcelona, Spain
| | - Patricia Pozo-Rosich
- Headache and Neurological Pain Research Group, Vall d'Hebron Institute of Research, Universitat Autònoma de Barcelona, Spain.,Headache Unit, Neurology Department, Vall d'Hebron University Hospital, Barcelona, Spain
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34
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Lee YX, Su PH, Do AQ, Tzeng CR, Hu YM, Chen CH, Chen CW, Liao CC, Chen LY, Weng YC, Wang HC, Lai HC. Cervical Secretion Methylation Is Associated with the Pregnancy Outcome of Frozen-Thawed Embryo Transfer. Int J Mol Sci 2023; 24:ijms24021726. [PMID: 36675243 PMCID: PMC9863254 DOI: 10.3390/ijms24021726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/06/2023] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
The causes of implantation failure remain a black box in reproductive medicine. The exact mechanism behind the regulation of endometrial receptivity is still unknown. Epigenetic modifications influence gene expression patterns and may alter the receptivity of human endometrium. Cervical secretions contain endometrial genetic material, which can be used as an indicator of the endometrial condition. This study evaluates the association between the cervical secretion gene methylation profile and pregnancy outcome in a frozen-thawed embryonic transfer (FET) cycle. Cervical secretions were collected from women who entered the FET cycle with a blastocyst transfer (36 pregnant and 36 non-pregnant women). The DNA methylation profiles of six candidate genes selected from the literature review were measured by quantitative methylation-specific PCR (qMSP). Bioinformatic analysis of six selected candidate genes showed significant differences in DNA methylation between receptive and pre-receptive endometrium. All candidate genes showed different degrees of correlation with the pregnancy outcomes in the logistic regression model. A machine learning approach showed that the combination of candidate genes' DNA methylation profiles could differentiate pregnant from non-pregnant samples with an accuracy as high as 86.67% and an AUC of 0.81. This study demonstrated the association between cervical secretion methylation profiles and pregnancy outcomes in an FET cycle and provides a basis for potential clinical application as a non-invasive method for implantation prediction.
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Affiliation(s)
- Yi-Xuan Lee
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 11030, Taiwan
- Taipei Fertility Center, Taipei 11030, Taiwan
- Translational Epigenetics Center, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
| | - Po-Hsuan Su
- Translational Epigenetics Center, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
- Department of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
| | - Anh Q. Do
- International Ph.D. Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei 110301, Taiwan
- Department of Obstetrics and Gynecology, Hai Phong University of Medicine and Pharmacy, Hai Phong 04254, Vietnam
| | - Chii-Ruei Tzeng
- Taipei Fertility Center, Taipei 11030, Taiwan
- Department of Obstetrics and Gynecology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11303, Taiwan
| | - Yu-Ming Hu
- Taipei Fertility Center, Taipei 11030, Taiwan
| | - Chi-Huang Chen
- Department of Obstetrics and Gynecology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11303, Taiwan
- Division of Reproductive Medicine, Department of Obstetrics and Gynecology, Taipei Medical University Hospital, Taipei 11030, Taiwan
| | - Chien-Wen Chen
- Department of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
| | - Chi-Chun Liao
- Department of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
| | - Lin-Yu Chen
- Translational Epigenetics Center, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
- Department of Obstetrics and Gynecology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11303, Taiwan
| | - Yu-Chun Weng
- Translational Epigenetics Center, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
| | - Hui-Chen Wang
- Department of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
- Department of Obstetrics and Gynecology, Tri-Service General Hospital, National Defense Medical Center, Taipei 11490, Taiwan
| | - Hung-Cheng Lai
- Graduate Institute of Clinical Medicine, College of Medicine, Taipei Medical University, Taipei 11030, Taiwan
- Translational Epigenetics Center, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
- Department of Obstetrics and Gynecology, Shuang Ho Hospital, Taipei Medical University, New Taipei 23504, Taiwan
- Department of Obstetrics and Gynecology, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11303, Taiwan
- Correspondence: or ; Tel.: +886-2-2249-0088 (ext. 8868)
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35
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Dapas M, Thompson EE, Wentworth-Sheilds W, Clay S, Visness CM, Calatroni A, Sordillo JE, Gold DR, Wood RA, Makhija M, Khurana Hershey GK, Sherenian MG, Gruchalla RS, Gill MA, Liu AH, Kim H, Kattan M, Bacharier LB, Rastogi D, Altman MC, Busse WW, Becker PM, Nicolae D, O’Connor GT, Gern JE, Jackson DJ, Ober C. Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings. PLoS Genet 2023; 19:e1010594. [PMID: 36638096 PMCID: PMC9879483 DOI: 10.1371/journal.pgen.1010594] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 01/26/2023] [Accepted: 12/23/2022] [Indexed: 01/14/2023] Open
Abstract
Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06-0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.
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Affiliation(s)
- Matthew Dapas
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | - Emma E. Thompson
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | | | - Selene Clay
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
| | | | | | - Joanne E. Sordillo
- Department of Population Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Diane R. Gold
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Robert A. Wood
- Department of Pediatrics, Johns Hopkins University Medical Center, Baltimore, Maryland, United States of America
| | - Melanie Makhija
- Division of Allergy and Immunology, Ann & Robert H. Lurie Children’s Hospital, Chicago, Illinois, United States of America
| | - Gurjit K. Khurana Hershey
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Michael G. Sherenian
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Division of Asthma Research, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
| | - Rebecca S. Gruchalla
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Michelle A. Gill
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Andrew H. Liu
- Department of Allergy and Immunology, Children’s Hospital Colorado, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Haejin Kim
- Department of Medicine, Henry Ford Health System, Detroit, Michigan, United States of America
| | - Meyer Kattan
- Columbia University College of Physicians and Surgeons, New York, New York, United States of America
| | - Leonard B. Bacharier
- Monroe Carell Jr. Children’s Hospital at Vanderbilt University Medical Center, Nashville, Tennessee, United States of America
| | - Deepa Rastogi
- Children’s National Health System, Washington, District of Columbia, United States of America
| | - Matthew C. Altman
- Department of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, United States of America
| | - William W. Busse
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Patrice M. Becker
- National Institute of Allergy and Infectious Diseases, Bethesda, Maryland, United States of America
| | - Dan Nicolae
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
| | - George T. O’Connor
- Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts, United States of America
| | - James E. Gern
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Daniel J. Jackson
- Department of Pediatrics and Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago Illinois, United States of America
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36
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De Riso G, Sarnataro A, Scala G, Cuomo M, Della Monica R, Amente S, Chiariotti L, Miele G, Cocozza S. MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data. NAR Genom Bioinform 2022; 4:lqac096. [PMID: 36601577 PMCID: PMC9803872 DOI: 10.1093/nargab/lqac096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/24/2022] [Accepted: 12/08/2022] [Indexed: 01/01/2023] Open
Abstract
DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.
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Affiliation(s)
- Giulia De Riso
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
| | - Antonella Sarnataro
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
| | - Giovanni Scala
- Department of Biology, University of Naples Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, Italy
| | - Mariella Cuomo
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145 Naples, Italy
| | - Rosa Della Monica
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145 Naples, Italy
| | - Stefano Amente
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
| | - Lorenzo Chiariotti
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
- CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145 Naples, Italy
| | - Gennaro Miele
- Department of Physics “E. Pancini”, University of Naples “Federico II”, Via Cinthia, 80126 Naples, Italy
- Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli, 80126 Naples, Italy
| | - Sergio Cocozza
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy
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37
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Jurmeister P, Glöß S, Roller R, Leitheiser M, Schmid S, Mochmann LH, Payá Capilla E, Fritz R, Dittmayer C, Friedrich C, Thieme A, Keyl P, Jarosch A, Schallenberg S, Bläker H, Hoffmann I, Vollbrecht C, Lehmann A, Hummel M, Heim D, Haji M, Harter P, Englert B, Frank S, Hench J, Paulus W, Hasselblatt M, Hartmann W, Dohmen H, Keber U, Jank P, Denkert C, Stadelmann C, Bremmer F, Richter A, Wefers A, Ribbat-Idel J, Perner S, Idel C, Chiariotti L, Della Monica R, Marinelli A, Schüller U, Bockmayr M, Liu J, Lund VJ, Forster M, Lechner M, Lorenzo-Guerra SL, Hermsen M, Johann PD, Agaimy A, Seegerer P, Koch A, Heppner F, Pfister SM, Jones DTW, Sill M, von Deimling A, Snuderl M, Müller KR, Forgó E, Howitt BE, Mertins P, Klauschen F, Capper D. DNA methylation-based classification of sinonasal tumors. Nat Commun 2022; 13:7148. [PMID: 36443295 PMCID: PMC9705411 DOI: 10.1038/s41467-022-34815-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 11/07/2022] [Indexed: 11/29/2022] Open
Abstract
The diagnosis of sinonasal tumors is challenging due to a heterogeneous spectrum of various differential diagnoses as well as poorly defined, disputed entities such as sinonasal undifferentiated carcinomas (SNUCs). In this study, we apply a machine learning algorithm based on DNA methylation patterns to classify sinonasal tumors with clinical-grade reliability. We further show that sinonasal tumors with SNUC morphology are not as undifferentiated as their current terminology suggests but rather reassigned to four distinct molecular classes defined by epigenetic, mutational and proteomic profiles. This includes two classes with neuroendocrine differentiation, characterized by IDH2 or SMARCA4/ARID1A mutations with an overall favorable clinical course, one class composed of highly aggressive SMARCB1-deficient carcinomas and another class with tumors that represent potentially previously misclassified adenoid cystic carcinomas. Our findings can aid in improving the diagnostic classification of sinonasal tumors and could help to change the current perception of SNUCs.
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Affiliation(s)
- Philipp Jurmeister
- grid.411095.80000 0004 0477 2585Institute of Pathology, Ludwig Maximilians University Hospital Munich, Munich, Germany ,grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584 German Cancer Consortium (DKTK), Partner Site Munich, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stefanie Glöß
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Renée Roller
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.484013.a0000 0004 6879 971XProteomics Platform, Berlin Institute of Health (BIH) and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
| | - Maximilian Leitheiser
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Simone Schmid
- grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Liliana H. Mochmann
- grid.411095.80000 0004 0477 2585Institute of Pathology, Ludwig Maximilians University Hospital Munich, Munich, Germany
| | - Emma Payá Capilla
- grid.411095.80000 0004 0477 2585Institute of Pathology, Ludwig Maximilians University Hospital Munich, Munich, Germany
| | - Rebecca Fritz
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Carsten Dittmayer
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Corinna Friedrich
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.419491.00000 0001 1014 0849MDC Graduate School, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany ,grid.7468.d0000 0001 2248 7639Humboldt Universität zu Berlin, Institute of Chemistry, Berlin, Germany
| | - Anne Thieme
- grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Philipp Keyl
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Armin Jarosch
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Simon Schallenberg
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Hendrik Bläker
- grid.411339.d0000 0000 8517 9062Institute of Pathology, University Hospital Leipzig, Leipzig, Germany
| | - Inga Hoffmann
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Claudia Vollbrecht
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Annika Lehmann
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Hummel
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Heim
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Mohamed Haji
- grid.484013.a0000 0004 6879 971XProteomics Platform, Berlin Institute of Health (BIH) and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
| | - Patrick Harter
- grid.7497.d0000 0004 0492 0584 German Cancer Consortium (DKTK), Partner Site Munich, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.7839.50000 0004 1936 9721Institute of Neurology (Edinger Institute), Goethe-University Frankfurt am Main, Frankfurt am Main, Germany ,grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, Frankfurt am Main, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Benjamin Englert
- grid.411095.80000 0004 0477 2585Institute of Neuropathology, Ludwig Maximilians University Hospital Munich, Munich, Germany
| | - Stephan Frank
- grid.410567.1Department of Neuropathology, Institute of Pathology, Basel University Hospital, Basel, Switzerland
| | - Jürgen Hench
- grid.410567.1Department of Neuropathology, Institute of Pathology, Basel University Hospital, Basel, Switzerland
| | - Werner Paulus
- grid.16149.3b0000 0004 0551 4246Institute of Neuropathology, University Hospital Münster, Münster, Germany
| | - Martin Hasselblatt
- grid.16149.3b0000 0004 0551 4246Institute of Neuropathology, University Hospital Münster, Münster, Germany
| | - Wolfgang Hartmann
- grid.16149.3b0000 0004 0551 4246Division of Translational Pathology, Gerhard-Domagk-Institute of Pathology, University Hospital Münster, Münster, Germany
| | - Hildegard Dohmen
- grid.8664.c0000 0001 2165 8627Institute of Neuropathology, University of Giessen, Giessen, Germany
| | - Ursula Keber
- grid.10253.350000 0004 1936 9756Institute of Neuropathology, Philipps-University, Marburg, Germany
| | - Paul Jank
- grid.10253.350000 0004 1936 9756Institute of Pathology, Philipps-University Marburg and University Hospital Marburg, Marburg, Germany
| | - Carsten Denkert
- grid.10253.350000 0004 1936 9756Institute of Pathology, Philipps-University Marburg and University Hospital Marburg, Marburg, Germany
| | - Christine Stadelmann
- grid.411984.10000 0001 0482 5331Institute for Neuropathology, University Medical Centre Göttingen, Göttingen, Germany
| | - Felix Bremmer
- grid.411984.10000 0001 0482 5331Institute of Pathology, University Medical Center, Göttingen, Germany
| | - Annika Richter
- grid.411984.10000 0001 0482 5331Institute of Pathology, University Medical Center, Göttingen, Germany
| | - Annika Wefers
- grid.5253.10000 0001 0328 4908Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.13648.380000 0001 2180 3484Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julika Ribbat-Idel
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany
| | - Sven Perner
- Institute of Pathology, University of Luebeck and University Hospital Schleswig-Holstein, Campus Luebeck, Luebeck, Germany ,grid.418187.30000 0004 0493 9170Pathology, Research Center Borstel, Leibniz Lung Center, Borstel, Germany ,grid.452624.3German Center for Lung Research (DZL), Partner Site Luebeck, Luebeck, Germany
| | - Christian Idel
- grid.412468.d0000 0004 0646 2097Department of Otorhinolaryngology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Lorenzo Chiariotti
- grid.4691.a0000 0001 0790 385XDipartimento di Medicina Molecolare e Biotecnologie Mediche, Università degli Studi di Napoli Federico II, Via S. Pansini 5, 80131 Naples, Italy ,grid.4691.a0000 0001 0790 385XCEINGE Biotecnologie Avanzate, 80145 Naples, Italy
| | - Rosa Della Monica
- grid.4691.a0000 0001 0790 385XCEINGE Biotecnologie Avanzate, 80145 Naples, Italy
| | - Alfredo Marinelli
- grid.4691.a0000 0001 0790 385XDepartment of Medicina Clinica e Chirurgia, University Federico II, Naples, Italy
| | - Ulrich Schüller
- grid.13648.380000 0001 2180 3484Institute of Neuropathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany ,grid.13648.380000 0001 2180 3484Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany ,grid.470174.1Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | - Michael Bockmayr
- grid.6363.00000 0001 2218 4662Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany ,grid.13648.380000 0001 2180 3484Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany ,grid.470174.1Research Institute Children’s Cancer Center Hamburg, Hamburg, Germany
| | - Jacklyn Liu
- grid.83440.3b0000000121901201UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT UK ,grid.83440.3b0000000121901201UCL Academic Head and Neck Centre, Division of Surgery and Interventional Science, University College London, London, UK
| | - Valerie J. Lund
- grid.83440.3b0000000121901201UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT UK ,grid.83440.3b0000000121901201UCL Academic Head and Neck Centre, Division of Surgery and Interventional Science, University College London, London, UK
| | - Martin Forster
- grid.83440.3b0000000121901201UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT UK ,grid.83440.3b0000000121901201UCL Academic Head and Neck Centre, Division of Surgery and Interventional Science, University College London, London, UK
| | - Matt Lechner
- grid.83440.3b0000000121901201UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT UK ,grid.83440.3b0000000121901201UCL Academic Head and Neck Centre, Division of Surgery and Interventional Science, University College London, London, UK
| | - Sara L. Lorenzo-Guerra
- grid.511562.4Department of Head and Neck Oncology, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Mario Hermsen
- grid.511562.4Department of Head and Neck Oncology, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Pascal D. Johann
- Swabian Childrens’ Cancer Center, University Childrens’ Hospital Augsburg and EU-RHAB Registry, Augsburg, Germany
| | - Abbas Agaimy
- grid.411668.c0000 0000 9935 6525Institute of Pathology, Friedrich-Alexander-University Erlangen-Nürnberg, University Hospital, Erlangen, Germany
| | - Philipp Seegerer
- grid.6734.60000 0001 2292 8254Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technical University of Berlin, Berlin, Germany
| | - Arend Koch
- grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Frank Heppner
- grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
| | - Stefan M. Pfister
- grid.510964.fHopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany ,grid.5253.10000 0001 0328 4908Department of Hematology and Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - David T. W. Jones
- grid.510964.fHopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584Division of Pediatric Glioma Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Sill
- grid.510964.fHopp Children’s Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
| | - Andreas von Deimling
- grid.5253.10000 0001 0328 4908Department of Neuropathology, University Hospital Heidelberg, Heidelberg, Germany ,grid.7497.d0000 0004 0492 0584Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matija Snuderl
- grid.240324.30000 0001 2109 4251Division of Neuropathology, NYU Langone Health, New York, USA ,grid.240324.30000 0001 2109 4251Laura and Isaac Perlmutter Cancer Center, NYU Langone Health, New York, USA ,grid.240324.30000 0001 2109 4251Division of Molecular Pathology and Diagnostics, NYU Langone Health, New York, USA
| | - Klaus-Robert Müller
- grid.6734.60000 0001 2292 8254Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technical University of Berlin, Berlin, Germany ,grid.222754.40000 0001 0840 2678Department of Artificial Intelligence, Korea University, Seoul, South Korea ,grid.419528.30000 0004 0491 9823Max-Planck-Institute for Informatics, Saarbrücken, Germany ,BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
| | - Erna Forgó
- grid.168010.e0000000419368956Stanford University School of Medicine, Stanford, CA USA
| | - Brooke E. Howitt
- grid.168010.e0000000419368956Stanford University School of Medicine, Stanford, CA USA
| | - Philipp Mertins
- grid.484013.a0000 0004 6879 971XProteomics Platform, Berlin Institute of Health (BIH) and Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
| | - Frederick Klauschen
- grid.411095.80000 0004 0477 2585Institute of Pathology, Ludwig Maximilians University Hospital Munich, Munich, Germany ,grid.7497.d0000 0004 0492 0584 German Cancer Consortium (DKTK), Partner Site Munich, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
| | - David Capper
- grid.7497.d0000 0004 0492 0584German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany ,grid.6363.00000 0001 2218 4662Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuropathology, Charitéplatz 1, Berlin, Germany
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38
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Wang Y, Xie H, Chang X, Hu W, Li M, Li Y, Liu H, Cheng H, Wang S, Zhou L, Shen D, Dou S, Ma R, Mao Y, Zhu H, Zhang X, Zheng Y, Ye X, Wen L, Kee K, Cui H, Tang F. Single-Cell Dissection of the Multiomic Landscape of High-Grade Serous Ovarian Cancer. Cancer Res 2022; 82:3903-3916. [PMID: 35969151 PMCID: PMC9627134 DOI: 10.1158/0008-5472.can-21-3819] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 04/30/2022] [Accepted: 08/09/2022] [Indexed: 01/07/2023]
Abstract
High-grade serous cancer (HGSC) is the most common subtype of ovarian cancer. HGSC is highly aggressive with poor patient outcomes, and a deeper understanding of HGSC tumorigenesis could help guide future treatment development. To systematically characterize the underlying pathologic mechanisms and intratumoral heterogeneity in human HGSC, we used an optimized single-cell multiomics sequencing technology to simultaneously analyze somatic copy-number alterations (SCNA), DNA methylation, chromatin accessibility, and transcriptome in individual cancer cells. Genes associated with interferon signaling, metallothioneins, and metabolism were commonly upregulated in ovarian cancer cells. Integrated multiomics analyses revealed that upregulation of interferon signaling and metallothioneins was influenced by both demethylation of their promoters and hypomethylation of satellites and LINE1, and potential key transcription factors regulating glycolysis using chromatin accessibility data were uncovered. In addition, gene expression and DNA methylation displayed similar patterns in matched primary and abdominal metastatic tumor cells of the same genetic lineage, suggesting that metastatic cells potentially preexist in the subclones of primary tumors. Finally, the lineages of cancer cells with higher residual DNA methylation levels and upregulated expression of CCN1 and HSP90AA1 presented greater metastatic potential. This study characterizes the critical genetic, epigenetic, and transcriptomic features and their mutual regulatory relationships in ovarian cancer, providing valuable resources for identifying new molecular mechanisms and potential therapeutic targets for HGSC. SIGNIFICANCE Integrated analysis of multiomic changes and epigenetic regulation in high-grade serous ovarian cancer provides insights into the molecular characteristics of this disease, which could help improve diagnosis and treatment.
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Affiliation(s)
- Yicheng Wang
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China
| | - Haoling Xie
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China
| | - Xiaohong Chang
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Wenqi Hu
- Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China
| | - Mengyao Li
- Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China
| | - Yi Li
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Huiping Liu
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Hongyan Cheng
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Shang Wang
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Ling Zhou
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Danhua Shen
- Department of Pathology, People's Hospital, Peking University, Beijing, China
| | - Sha Dou
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Ruiqiong Ma
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Yunuo Mao
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China
| | - Honglan Zhu
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Xiaobo Zhang
- Department of Pathology, People's Hospital, Peking University, Beijing, China
| | - Yuxuan Zheng
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China
| | - Xue Ye
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China
| | - Lu Wen
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China
| | - Kehkooi Kee
- Center for Stem Cell Biology and Regenerative Medicine, Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China.,Corresponding Authors: Fuchou Tang, Beijing Advanced Innovation Center for Genomics, School of Life Sciences, Peking University, Beijing 100871, China. E-mail: ; Heng Cui, Peking University People's Hospital, 11 Xizhimen South Street, Xicheng District, Beijing 100044, China. E-mail: ; and Kehkooi Kee, Tsinghua University, 30 Shuangqing Road, Beijing 100084, China. E-mail:
| | - Heng Cui
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Center of Gynecologic Oncology, People's Hospital, Peking University, Beijing, China.,Corresponding Authors: Fuchou Tang, Beijing Advanced Innovation Center for Genomics, School of Life Sciences, Peking University, Beijing 100871, China. E-mail: ; Heng Cui, Peking University People's Hospital, 11 Xizhimen South Street, Xicheng District, Beijing 100044, China. E-mail: ; and Kehkooi Kee, Tsinghua University, 30 Shuangqing Road, Beijing 100084, China. E-mail:
| | - Fuchou Tang
- School of Life Sciences, Biomedical Pioneering Innovation Center, Department of Obstetrics and Gynecology, People's Hospital, Peking University, Beijing, China.,Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Peking University, Beijing, China.,Corresponding Authors: Fuchou Tang, Beijing Advanced Innovation Center for Genomics, School of Life Sciences, Peking University, Beijing 100871, China. E-mail: ; Heng Cui, Peking University People's Hospital, 11 Xizhimen South Street, Xicheng District, Beijing 100044, China. E-mail: ; and Kehkooi Kee, Tsinghua University, 30 Shuangqing Road, Beijing 100084, China. E-mail:
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39
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Roopnarinesingh XR, Porter H, Giles C, Brown C, Georgescu C, Wren J. Multi-tissue DNA methylation microarray signature is predictive of gene function. Epigenetics 2022; 17:1404-1418. [PMID: 35152835 PMCID: PMC9586602 DOI: 10.1080/15592294.2022.2036411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/10/2022] [Accepted: 01/25/2022] [Indexed: 11/03/2022] Open
Abstract
Background Transcriptional correlation networks derived from publicly available gene expression microarrays have been previously shown to be predictive of known gene functions, but less is known about the predictive capacity of correlated DNA methylation at CpG sites. Guilt-by-association co-expression methods can adapted for use with DNA methylation when a representative methylation value is created for each gene. We examine how methylation compares to expression in predicting Gene Ontology terms using both co-methylation and traditional machine learning approaches across different types of representative methylation values per gene. Methods We perform guilt-by-association gene function prediction with a suite of models called Methylation Array Network Analysis, using a network of correlated methylation values derived from over 24,000 samples. In generating the correlation matrix, the performance of different methods of collapsing probe-level data effect on the resulting gene function predictions was compared, along with the use of different regions surrounding the gene of interest. Results Using mean comethylation of a given gene to its annotated term had an overall highest prediction macro-AUC of 0.60 using mean gene body methylation, across all Gene Ontology terms. This was increased using the logistic regression approach with the highest macro-AUC of 0.82 using mean gene body methylation, compared to the naive predictor of 0.72. Conclusion Genes correlated in their methylation state are functionally related. Genes clustered in co-methylation space were enriched for chromatin state, PRC2, immune response, and development-related terms.
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Affiliation(s)
- Xiavan Renaldo Roopnarinesingh
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Biochemistry and Molecular Biology Dept, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Hunter Porter
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Oklahoma Center for Neuroscience, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Cory Giles
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Chase Brown
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Oklahoma Center for Neuroscience, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Constantin Georgescu
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Jonathan Wren
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Biochemistry and Molecular Biology Dept, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Oklahoma Center for Neuroscience, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Stephenson Cancer Center, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
- Department of Geriatric Medicine, University of Oklahoma Health Sciences Center, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
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40
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Marttila S, Tamminen H, Rajić S, Mishra PP, Lehtimäki T, Raitakari O, Kähönen M, Kananen L, Jylhävä J, Hägg S, Delerue T, Peters A, Waldenberger M, Kleber ME, März W, Luoto R, Raitanen J, Sillanpää E, Laakkonen EK, Heikkinen A, Ollikainen M, Raitoharju E. Methylation status of VTRNA2-1/ nc886 is stable across populations, monozygotic twin pairs and in majority of tissues. Epigenomics 2022; 14:1105-1124. [PMID: 36200237 DOI: 10.2217/epi-2022-0228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Gerontology Research Center, Tampere University, Tampere, 33014, Finland
| | - Hely Tamminen
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku & Turku University Hospital, Turku, 20014, Finland.,Research Centre of Applied & Preventive Cardiovascular Medicine, University of Turku, Turku, 20014, Finland.,Department of Clinical Physiology & Nuclear Medicine, Turku University Hospital, Turku, 20014, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
| | - Laura Kananen
- Faculty of Medicine & Health Technology, & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520,Finland.,Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sara Hägg
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,Competence Cluster for Nutrition & Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, 07743, Germany.,SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg, 86156, Germany.,Clinical Institute of Medical & Chemical Laboratory Diagnostics, Medical University of Graz, Graz, 8010, Austria
| | - Riitta Luoto
- The Social Insurance Institute of Finland (Kela), Helsinki, 00250, Finland.,The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland
| | - Jani Raitanen
- The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland.,Faculty of Social Sciences (Health Sciences), Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Elina Sillanpää
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland.,Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Eija K Laakkonen
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
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41
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Zhu Y, Lussier AA, Smith ADAC, Simpkin AJ, Suderman MJ, Walton E, Relton CL, Dunn EC. Examining the epigenetic mechanisms of childhood adversity and sensitive periods: A gene set-based approach. Psychoneuroendocrinology 2022; 144:105854. [PMID: 35914392 PMCID: PMC9885844 DOI: 10.1016/j.psyneuen.2022.105854] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Sensitive periods are developmental stages of heightened plasticity when life experiences, including exposure to childhood adversity, have the potential to exert more lasting impacts. Epigenetic mechanisms, including DNA methylation (DNAm), may provide a pathway through which adversity induces long-term biological changes. DNAm shifts may be more likely to occur during sensitive periods, especially within genes that regulate the timing of sensitive periods. Here, we investigated the possibility that childhood adversity during specific life stages is associated with DNAm changes in genes known to regulate the timing and duration of sensitive periods. METHODS Genome-wide DNAm profiles came from the Avon Longitudinal Study of Parents and Children (n = 785). We first used principal component analysis (PCA) to summarize DNAm variation across 530 CpG sites mapped to the promoters of 58 genes previously-identified as regulating sensitive periods. Gene-level DNAm summaries were calculated for genes regulating sensitive period opening (ngenes = 15), closing (ngenes = 36), and expression (ngenes = 8). We then performed linear discriminant analysis (LDA) to test associations between seven types of parent-reported, time-varying measures of exposure to childhood adversity and DNAm principal components. To our knowledge, this is the first time LDA has been applied to analyze functionally grouped DNAm data to characterize associations between an environmental exposure and epigenetic differences. RESULTS Suggestive evidence emerged for associations between sexual or physical abuse as well as financial hardship during middle childhood, and DNAm of genetic pathways regulating sensitive period opening and expression. However, no statistically significant associations were identified after multiple testing correction. CONCLUSIONS Our gene set-based method combining PCA and LDA complements epigenome-wide approaches. Although our results were largely null, these findings provide a proof-of-concept for studying time-varying exposures and gene- or pathway-level epigenetic modifications.
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Affiliation(s)
- Yiwen Zhu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
| | - Alexandre A Lussier
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States
| | - Andrew D A C Smith
- Mathematics and Statistics Research Group, University of the West of England, Bristol, UK
| | - Andrew J Simpkin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Ireland
| | - Matthew J Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Erin C Dunn
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, United States; Harvard Center on the Developing Child, Cambridge, MA, United States.
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42
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Liu YH, Hu CM, Hsu YS, Lee WH. Interplays of glucose metabolism and KRAS mutation in pancreatic ductal adenocarcinoma. Cell Death Dis 2022; 13:817. [PMID: 36151074 PMCID: PMC9508091 DOI: 10.1038/s41419-022-05259-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 09/08/2022] [Accepted: 09/12/2022] [Indexed: 01/23/2023]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and deadliest cancer worldwide. The primary reasons for this are the lack of early detection methods and targeted therapy. Emerging evidence highlights the metabolic addiction of cancer cells as a potential target to combat PDAC. Oncogenic mutations of KRAS are the most common triggers that drive glucose uptake and utilization via metabolic reprogramming to support PDAC growth. Conversely, high glucose levels in the pancreatic microenvironment trigger genome instability and de novo mutations, including KRASG12D, in pancreatic cells through metabolic reprogramming. Here, we review convergent and diverse metabolic networks related to oncogenic KRAS mutations between PDAC initiation and progression, emphasizing the interplay among oncogenic mutations, glucose metabolic reprogramming, and the tumor microenvironment. Recognizing cancer-related glucose metabolism will provide a better strategy to prevent and treat the high risk PDAC population.
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Affiliation(s)
- Yu-Huei Liu
- grid.254145.30000 0001 0083 6092Drug Development Center, China Medical University, Taichung, Taiwan ,grid.254145.30000 0001 0083 6092Graduate Institute of Integrated Medicine, China Medical University, Taichung, Taiwan ,grid.411508.90000 0004 0572 9415Department of Medical Genetics and Medical Research, China Medical University Hospital, Taichung, Taiwan
| | - Chun-Mei Hu
- grid.254145.30000 0001 0083 6092Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan ,grid.28665.3f0000 0001 2287 1366Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Yuan-Sheng Hsu
- grid.254145.30000 0001 0083 6092Drug Development Center, China Medical University, Taichung, Taiwan ,grid.254145.30000 0001 0083 6092Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan ,grid.28665.3f0000 0001 2287 1366Genomics Research Center, Academia Sinica, Taipei, Taiwan
| | - Wen-Hwa Lee
- grid.254145.30000 0001 0083 6092Drug Development Center, China Medical University, Taichung, Taiwan ,grid.28665.3f0000 0001 2287 1366Genomics Research Center, Academia Sinica, Taipei, Taiwan ,grid.266093.80000 0001 0668 7243Department of Biological Chemistry, University of California, Irvine, CA USA
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43
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Carratto TMT, Moraes VMS, Recalde TSF, Oliveira MLGD, Teixeira Mendes-Junior C. Applications of massively parallel sequencing in forensic genetics. Genet Mol Biol 2022; 45:e20220077. [PMID: 36121926 PMCID: PMC9514793 DOI: 10.1590/1678-4685-gmb-2022-0077] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 07/15/2022] [Indexed: 11/22/2022] Open
Abstract
Massively parallel sequencing, also referred to as next-generation sequencing, has positively changed DNA analysis, allowing further advances in genetics. Its capability of dealing with low quantity/damaged samples makes it an interesting instrument for forensics. The main advantage of MPS is the possibility of analyzing simultaneously thousands of genetic markers, generating high-resolution data. Its detailed sequence information allowed the discovery of variations in core forensic short tandem repeat loci, as well as the identification of previous unknown polymorphisms. Furthermore, different types of markers can be sequenced in a single run, enabling the emergence of DIP-STRs, SNP-STR haplotypes, and microhaplotypes, which can be very useful in mixture deconvolution cases. In addition, the multiplex analysis of different single nucleotide polymorphisms can provide valuable information about identity, biogeographic ancestry, paternity, or phenotype. DNA methylation patterns, mitochondrial DNA, mRNA, and microRNA profiling can also be analyzed for different purposes, such as age inference, maternal lineage analysis, body-fluid identification, and monozygotic twin discrimination. MPS technology also empowers the study of metagenomics, which analyzes genetic material from a microbial community to obtain information about individual identification, post-mortem interval estimation, geolocation inference, and substrate analysis. This review aims to discuss the main applications of MPS in forensic genetics.
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Affiliation(s)
- Thássia Mayra Telles Carratto
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | - Vitor Matheus Soares Moraes
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
| | | | | | - Celso Teixeira Mendes-Junior
- Universidade de São Paulo, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Departamento de Química, Laboratório de Pesquisas Forenses e Genômicas, Ribeirão Preto, SP, Brazil
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44
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Lamare FA, Khongsti S, Marthong L, Ghosh S, Chenkual S, Dkhar H, Maitra A, Ghosh S. Genome-wide DNA methylation profiling of stomach cancer in the ethnic population of Mizoram, North East India. Genomics 2022; 114:110478. [PMID: 36064073 DOI: 10.1016/j.ygeno.2022.110478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/10/2022] [Accepted: 08/31/2022] [Indexed: 12/01/2022]
Abstract
Stomach cancer is the fifth most common cancer in terms of prevalence and incidence and the fourth leading cause of mortality in men and women worldwide. It is well-established that aberrant DNA methylation in cells can lead to carcinogenesis. The primary objective of our study was to investigate the aberrant DNA methylation status of genes associated with stomach cancer with a particular reference to the ethnic population of Mizoram, North East India. The site-level analysis identified 2883 CpG sites differentially methylated, representing ~922 genes. Out of which 476 Differentially Methylated Positions (DMPs) were promoter-associated, 452 DMPs were hypermethylated, and 24 were hypomethylated. The region-level analysis identified 462 Differentially Methylated Regions (DMRs) corresponding to ~320 genes, of which ~281 genes were hypermethylated and ~ 40 genes were hypomethylated. TCGA analysis showed that some of the genes had been previously implicated in other cancers including stomach cancer. Five hypermethylated genes were selected as candidate genes for further investigations and they have shown to be novel and could serve as candidate hypermethylation biomarkers for stomach cancer in this particular ethnic group.
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Affiliation(s)
- F A Lamare
- Department of Zoology, North-Eastern Hill University (NEHU), Shillong, India
| | - S Khongsti
- Department of Zoology, North-Eastern Hill University (NEHU), Shillong, India
| | - L Marthong
- Department of Zoology, North-Eastern Hill University (NEHU), Shillong, India
| | - S Ghosh
- National Institute of Biomedical Genomics (NIBMG), Kalyani, West Bengal, India
| | | | - H Dkhar
- Nazareth Hospital, Shillong, India
| | - A Maitra
- National Institute of Biomedical Genomics (NIBMG), Kalyani, West Bengal, India
| | - S Ghosh
- Department of Zoology, North-Eastern Hill University (NEHU), Shillong, India.
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45
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Zuo Y, Zhong J, Bai H, Xu B, Wang Z, Li W, Chen Y, Jin S, Wang S, Wang X, Wan R, Xu J, Fei K, Han J, Yang Z, Bao H, Shao Y, Ying J, Song Q, Duan J, Wang J. Genomic and epigenomic profiles distinguish pulmonary enteric adenocarcinoma from lung metastatic colorectal cancer. EBioMedicine 2022; 82:104165. [PMID: 35901658 PMCID: PMC9334343 DOI: 10.1016/j.ebiom.2022.104165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/28/2022] [Accepted: 06/30/2022] [Indexed: 11/16/2022] Open
Affiliation(s)
- Ying Zuo
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jia Zhong
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Hua Bai
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bin Xu
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhijie Wang
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Weihua Li
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yedan Chen
- Nanjing Geneseeq Technology Inc., Nanjing, China
| | - Shi Jin
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, China
| | - Shuhang Wang
- GCP Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xin Wang
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Rui Wan
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiachen Xu
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Kailun Fei
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Jiefei Han
- Department of Neuro-oncology, Cancer Center Beijing Tiantan Hospital, Capital Medical University, China
| | - Zhenlin Yang
- Thoracic Surgery Department, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Hua Bao
- Nanjing Geneseeq Technology Inc., Nanjing, China
| | - Yang Shao
- Nanjing Geneseeq Technology Inc., Nanjing, China; School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jianming Ying
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Qibin Song
- Cancer center, Renmin Hospital of Wuhan University, Wuhan, China.
| | - Jianchun Duan
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
| | - Jie Wang
- State Key Laboratory of Molecular Oncology, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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46
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Derakhshan M, Kessler NJ, Ishida M, Demetriou C, Brucato N, Moore G, Fall CHD, Chandak GR, Ricaut FX, Prentice A, Hellenthal G, Silver M. Tissue- and ethnicity-independent hypervariable DNA methylation states show evidence of establishment in the early human embryo. Nucleic Acids Res 2022; 50:6735-6752. [PMID: 35713545 PMCID: PMC9749461 DOI: 10.1093/nar/gkac503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/06/2022] [Accepted: 05/27/2022] [Indexed: 12/24/2022] Open
Abstract
We analysed DNA methylation data from 30 datasets comprising 3474 individuals, 19 tissues and 8 ethnicities at CpGs covered by the Illumina450K array. We identified 4143 hypervariable CpGs ('hvCpGs') with methylation in the top 5% most variable sites across multiple tissues and ethnicities. hvCpG methylation was influenced but not determined by genetic variation, and was not linked to probe reliability, epigenetic drift, age, sex or cell heterogeneity effects. hvCpG methylation tended to covary across tissues derived from different germ-layers and hvCpGs were enriched for proximity to ERV1 and ERVK retrovirus elements. hvCpGs were also enriched for loci previously associated with periconceptional environment, parent-of-origin-specific methylation, and distinctive methylation signatures in monozygotic twins. Together, these properties position hvCpGs as strong candidates for studying how stochastic and/or environmentally influenced DNA methylation states which are established in the early embryo and maintained stably thereafter can influence life-long health and disease.
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Affiliation(s)
| | - Noah J Kessler
- Department of Genetics, University of Cambridge,
Cambridge CB2 3EH, UK
| | - Miho Ishida
- UCL Great Ormond Street Institute of Child Health, UK
| | | | - Nicolas Brucato
- Laboratoire Évolution and Diversité Biologique (EDB UMR 5174), Université
de Toulouse Midi-Pyrénées, CNRS, IRD, UPS,Toulouse, France
| | | | - Caroline H D Fall
- MRC Lifecourse Epidemiology Unit, University of Southampton,
Southampton, UK
| | - Giriraj R Chandak
- Genomic Research on Complex Diseases (GRC Group), CSIR-Centre for Cellular
and Molecular Biology,Hyderabad, India
| | - Francois-Xavier Ricaut
- Laboratoire Évolution and Diversité Biologique (EDB UMR 5174), Université
de Toulouse Midi-Pyrénées, CNRS, IRD, UPS,Toulouse, France
| | - Andrew M Prentice
- Medical Research Council Unit The Gambia at the London School of Hygiene
and Tropical Medicine, The Gambia
| | - Garrett Hellenthal
- UCL Genetics Institute, University College London,
Gower Street, London WC1E 6BT, UK
| | - Matt J Silver
- London School of Hygiene and Tropical Medicine, UK
- Medical Research Council Unit The Gambia at the London School of Hygiene
and Tropical Medicine, The Gambia
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47
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Gore S, Azad RK. CancerNet: a unified deep learning network for pan-cancer diagnostics. BMC Bioinformatics 2022; 23:229. [PMID: 35698059 PMCID: PMC9195411 DOI: 10.1186/s12859-022-04783-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 06/06/2022] [Indexed: 11/10/2022] Open
Abstract
Background Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technological advances in machine learning or artificial intelligence to design a novel framework for cancer diagnostics. Our proposed framework detects cancers and their tissues of origin using a unified model of cancers encompassing 33 cancers represented in The Cancer Genome Atlas (TCGA). Our model exploits the learned features of different cancers reflected in the respective dysregulated epigenomes, which arise early in carcinogenesis and differ remarkably between different cancer types or subtypes, thus holding a great promise in early cancer detection. Results Our comprehensive assessment of the proposed model on the 33 different tissues of origin demonstrates its ability to detect and classify cancers to a high accuracy (> 99% overall F-measure). Furthermore, our model distinguishes cancers from pre-cancerous lesions to metastatic tumors and discriminates between hypomethylation changes due to age related epigenetic drift and true cancer. Conclusions Beyond detection of primary cancers, our proposed computational model also robustly detects tissues of origin of secondary cancers, including metastatic cancers, second primary cancers, and cancers of unknown primaries. Our assessment revealed the ability of this model to characterize pre-cancer samples, a significant step forward in early cancer detection. Deployed broadly this model can deliver accurate diagnosis for a greatly expanded target patient population. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04783-y.
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Affiliation(s)
- Steven Gore
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA
| | - Rajeev K Azad
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA. .,Department of Mathematics, University of North Texas, Denton, TX, 76203, USA.
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48
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Woltering N, Albers A, Müther M, Stummer W, Paulus W, Hasselblatt M, Holling M, Thomas C. DNA
methylation profiling of central nervous system hemangioblastomas identifies two distinct subgroups. Brain Pathol 2022; 32:e13083. [PMID: 35637626 PMCID: PMC9616087 DOI: 10.1111/bpa.13083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/10/2022] [Indexed: 12/01/2022] Open
Abstract
Hemangioblastomas (HBs) of the central nervous system are highly vascular neoplasms that occur sporadically or as a manifestation of von Hippel–Lindau (VHL) disease. Despite their benign nature, HBs are clinically heterogeneous and can be associated with significant morbidity due to mass effects of peritumoral cysts or tumor progression. Underlying molecular factors involved in HB tumor biology remain elusive. We investigated genome‐wide DNA methylation profiles and clinical and histopathological features in a series of 47 HBs from 42 patients, including 28 individuals with VHL disease. Thirty tumors occurred in the cerebellum, 8 in the brainstem and 8 HBs were of spinal location, while 1 HB was located in the cerebrum. Histologically, 12 HBs (26%) belonged to the cellular subtype and exclusively occurred in the cerebellum, whereas 35 HBs were reticular (74%). Unsupervised clustering and dimensionality reduction of DNA methylation profiles revealed two distinct subgroups. Methylation cluster 1 comprised 30 HBs of mainly cerebellar location (29/30, 97%), whereas methylation cluster 2 contained 17 HBs predominantly located in non‐cerebellar compartments (16/17, 94%). The sum of chromosomal regions being affected by copy‐number alterations was significantly higher in methylation cluster 1 compared to cluster 2 (mean 262 vs. 109 Mb, p = 0.001). Of note, loss of chromosome 6 occurred in 9/30 tumors (30%) of methylation cluster 1 and was not observed in cluster 2 tumors (p = 0.01). No relevant methylation differences between sporadic and VHL‐related HBs or cystic and non‐cystic HBs could be detected. Deconvolution of the bulk DNA methylation profiles revealed four methylation components that were associated with the two methylation clusters suggesting cluster‐specific cell‐type compositions. In conclusion, methylation profiling of HBs reveals 2 distinct subgroups that mainly associate with anatomical location, cytogenetic profiles and differences in cell type composition, potentially reflecting different cells of origin.
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Affiliation(s)
- Niklas Woltering
- Institute of Neuropathology University Hospital Münster Münster Germany
| | - Anne Albers
- Institute of Neuropathology University Hospital Münster Münster Germany
| | - Michael Müther
- Department of Neurosurgery University Hospital Münster Münster Germany
| | - Walter Stummer
- Department of Neurosurgery University Hospital Münster Münster Germany
| | - Werner Paulus
- Institute of Neuropathology University Hospital Münster Münster Germany
| | | | - Markus Holling
- Department of Neurosurgery University Hospital Münster Münster Germany
| | - Christian Thomas
- Institute of Neuropathology University Hospital Münster Münster Germany
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49
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de Souza MM, Niciura SCM, Rocha MIP, Pan Z, Zhou H, Bruscadin JJ, da Silva Diniz WJ, Afonso J, de Oliveira PSN, Mourão GB, Zerlotini A, Coutinho LL, Koltes JE, de Almeida Regitano LC. DNA methylation may affect beef tenderness through signal transduction in Bos indicus. Epigenetics Chromatin 2022; 15:15. [PMID: 35562812 PMCID: PMC9107245 DOI: 10.1186/s13072-022-00449-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 04/12/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Beef tenderness is a complex trait of economic importance for the beef industry. Understanding the epigenetic mechanisms underlying this trait may help improve the accuracy of breeding programs. However, little is known about epigenetic effects on Bos taurus muscle and their implications in tenderness, and no studies have been conducted in Bos indicus. RESULTS Comparing methylation profile of Bos indicus skeletal muscle with contrasting beef tenderness at 14 days after slaughter, we identified differentially methylated cytosines and regions associated with this trait. Interestingly, muscle that became tender beef had higher levels of hypermethylation compared to the tough group. Enrichment analysis of predicted target genes suggested that differences in methylation between tender and tough beef may affect signal transduction pathways, among which G protein signaling was a key pathway. In addition, different methylation levels were found associated with expression levels of GNAS, PDE4B, EPCAM and EBF3 genes. The differentially methylated elements correlated with EBF3 and GNAS genes overlapped CpG islands and regulatory elements. GNAS, a complex imprinted gene, has a key role on G protein signaling pathways. Moreover, both G protein signaling pathway and the EBF3 gene regulate muscle homeostasis, relaxation, and muscle cell-specificity. CONCLUSIONS We present differentially methylated loci that may be of interest to decipher the epigenetic mechanisms affecting tenderness. Supported by the previous knowledge about regulatory elements and gene function, the methylation data suggests EBF3 and GNAS as potential candidate genes and G protein signaling as potential candidate pathway associated with beef tenderness via methylation.
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Affiliation(s)
- Marcela Maria de Souza
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Pecuária Sudeste, São Carlos, Brazil.,Department of Animal Science, Iowa State University, Ames, USA
| | | | - Marina Ibelli Pereira Rocha
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Pecuária Sudeste, São Carlos, Brazil.,Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, Brazil
| | - Zhangyuan Pan
- Department of Animal Science, University of California, Davis, CA, USA
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA, USA
| | - Jennifer Jessica Bruscadin
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Pecuária Sudeste, São Carlos, Brazil.,Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, Brazil
| | - Wellison Jarles da Silva Diniz
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Pecuária Sudeste, São Carlos, Brazil.,Department of Animal Science, Auburn University, Auburn, Alabama, USA
| | - Juliana Afonso
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Pecuária Sudeste, São Carlos, Brazil
| | | | - Gerson B Mourão
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil
| | - Adhemar Zerlotini
- Embrapa Informática Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, Brazil
| | - Luiz Lehmann Coutinho
- Department of Animal Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, Brazil
| | - James E Koltes
- Department of Animal Science, Iowa State University, Ames, USA
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50
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Age-Related DNA Methylation in Normal Kidney Tissue Identifies Epigenetic Cancer Risk Susceptibility Loci in the ANKRD34B and ZIC1 Genes. Int J Mol Sci 2022; 23:ijms23105327. [PMID: 35628134 PMCID: PMC9141100 DOI: 10.3390/ijms23105327] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023] Open
Abstract
Both age-dependent and age-independent alteration of DNA methylation in human tissues are functionally associated with the development of many malignant and non-malignant human diseases. TCGA-KIRC data were biometrically analyzed to identify new loci with age-dependent DNA methylation that may contribute to tumor risk in normal kidney tissue. ANKRD34B and ZIC1 were evaluated as candidate genes by pyrosequencing of 539 tissues, including 239 normal autopsy, 157 histopathologically tumor-adjacent normal, and 143 paired tumor kidney samples. All candidate CpG loci demonstrated a strong correlation between relative methylation levels and age (R = 0.70−0.88, p < 2 × 10−16) and seven out of 10 loci were capable of predicting chronological age in normal kidney tissues, explaining 84% of the variance (R = 0.92). Moreover, significantly increased age-independent methylation was found for 9 out of 10 CpG loci in tumor-adjacent tissues, compared to normal autopsy tissues (p = 0.001−0.028). Comparing tumor and paired tumor-adjacent tissues revealed two patient clusters showing hypermethylation, one cluster without significant changes in methylation, and a smaller cluster demonstrating hypomethylation in the tumors (p < 1 × 10−10). Taken together, our results show the presence of additional methylation risk factors besides age for renal cancer in normal kidney tissue. Concurrent tumor-specific hypermethylation suggests a subset of these loci are candidates for epigenetic renal cancer susceptibility.
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